---
library_name: sklearn
tags:
- sklearn
- skops
- tabular-classification
widget:
  structuredData:
    attribute_0:
    - material_7
    - material_7
    - material_7
    attribute_1:
    - material_8
    - material_8
    - material_5
    attribute_2:
    - 9
    - 9
    - 6
    attribute_3:
    - 5
    - 5
    - 6
    loading:
    - 150.15
    - 106.3
    - 117.52
    measurement_0:
    - 6
    - 11
    - 4
    measurement_1:
    - 7
    - 4
    - 9
    measurement_10:
    - 15.888
    - 15.56
    - 18.49
    measurement_11:
    - 21.623
    - 17.233
    - 20.193
    measurement_12:
    - 12.83
    - 12.926
    - 14.127
    measurement_13:
    - 14.738
    - 14.367
    - 15.185
    measurement_14:
    - 18.506
    - 16.302
    - 16.657
    measurement_15:
    - 14.16
    - 15.018
    - 13.326
    measurement_16:
    - 15.266
    - 18.297
    - 17.467
    measurement_17:
    - 674.165
    - 604.836
    - 648.023
    measurement_2:
    - 11
    - 4
    - 9
    measurement_3:
    - 19.637
    - 18.217
    - 19.325
    measurement_4:
    - 12.55
    - 10.627
    - 10.092
    measurement_5:
    - 17.119
    - 17.74
    - 17.218
    measurement_6:
    - NaN
    - 17.295
    - 17.962
    measurement_7:
    - 10.958
    - 11.732
    - 9.274
    measurement_8:
    - 17.93
    - 17.591
    - 18.653
    measurement_9:
    - NaN
    - 12.689
    - 13.149
    product_code:
    - A
    - A
    - D
---

# Model description

This is a DecisionTreeClassifier model built for Kaggle Tabular Playground Series August 2022, trained on supersoaker production failures dataset.

## Intended uses & limitations

This model is not ready to be used in production.

## Training Procedure

### Hyperparameters

The model is trained with below hyperparameters.

<details>
<summary> Click to expand </summary>

| Hyperparameter                                                  | Value                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
|-----------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| memory                                                          |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| steps                                                           | [('transformation', ColumnTransformer(transformers=[('loading_missing_value_imputer',
                                 SimpleImputer(), ['loading']),
                                ('numerical_missing_value_imputer',
                                 SimpleImputer(),
                                 ['loading', 'measurement_3', 'measurement_4',
                                  'measurement_5', 'measurement_6',
                                  'measurement_7', 'measurement_8',
                                  'measurement_9', 'measurement_10',
                                  'measurement_11', 'measurement_12',
                                  'measurement_13', 'measurement_14',
                                  'measurement_15', 'measurement_16',
                                  'measurement_17']),
                                ('attribute_0_encoder', OneHotEncoder(),
                                 ['attribute_0']),
                                ('attribute_1_encoder', OneHotEncoder(),
                                 ['attribute_1']),
                                ('product_code_encoder', OneHotEncoder(),
                                 ['product_code'])])), ('model', DecisionTreeClassifier(max_depth=4))]                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| verbose                                                         | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation                                                  | ColumnTransformer(transformers=[('loading_missing_value_imputer',
                                 SimpleImputer(), ['loading']),
                                ('numerical_missing_value_imputer',
                                 SimpleImputer(),
                                 ['loading', 'measurement_3', 'measurement_4',
                                  'measurement_5', 'measurement_6',
                                  'measurement_7', 'measurement_8',
                                  'measurement_9', 'measurement_10',
                                  'measurement_11', 'measurement_12',
                                  'measurement_13', 'measurement_14',
                                  'measurement_15', 'measurement_16',
                                  'measurement_17']),
                                ('attribute_0_encoder', OneHotEncoder(),
                                 ['attribute_0']),
                                ('attribute_1_encoder', OneHotEncoder(),
                                 ['attribute_1']),
                                ('product_code_encoder', OneHotEncoder(),
                                 ['product_code'])])                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| model                                                           | DecisionTreeClassifier(max_depth=4)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| transformation__n_jobs                                          |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__remainder                                       | drop                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__sparse_threshold                                | 0.3                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| transformation__transformer_weights                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__transformers                                    | [('loading_missing_value_imputer', SimpleImputer(), ['loading']), ('numerical_missing_value_imputer', SimpleImputer(), ['loading', 'measurement_3', 'measurement_4', 'measurement_5', 'measurement_6', 'measurement_7', 'measurement_8', 'measurement_9', 'measurement_10', 'measurement_11', 'measurement_12', 'measurement_13', 'measurement_14', 'measurement_15', 'measurement_16', 'measurement_17']), ('attribute_0_encoder', OneHotEncoder(), ['attribute_0']), ('attribute_1_encoder', OneHotEncoder(), ['attribute_1']), ('product_code_encoder', OneHotEncoder(), ['product_code'])] |
| transformation__verbose                                         | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation__verbose_feature_names_out                       | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__loading_missing_value_imputer                   | SimpleImputer()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__numerical_missing_value_imputer                 | SimpleImputer()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__attribute_0_encoder                             | OneHotEncoder()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__attribute_1_encoder                             | OneHotEncoder()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__product_code_encoder                            | OneHotEncoder()                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__loading_missing_value_imputer__add_indicator    | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation__loading_missing_value_imputer__copy             | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__loading_missing_value_imputer__fill_value       |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__loading_missing_value_imputer__missing_values   | nan                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| transformation__loading_missing_value_imputer__strategy         | mean                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__loading_missing_value_imputer__verbose          | 0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| transformation__numerical_missing_value_imputer__add_indicator  | False                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation__numerical_missing_value_imputer__copy           | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__numerical_missing_value_imputer__fill_value     |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__numerical_missing_value_imputer__missing_values | nan                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| transformation__numerical_missing_value_imputer__strategy       | mean                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__numerical_missing_value_imputer__verbose        | 0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| transformation__attribute_0_encoder__categories                 | auto                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__attribute_0_encoder__drop                       |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__attribute_0_encoder__dtype                      | <class 'numpy.float64'>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| transformation__attribute_0_encoder__handle_unknown             | error                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation__attribute_0_encoder__sparse                     | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__attribute_1_encoder__categories                 | auto                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__attribute_1_encoder__drop                       |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__attribute_1_encoder__dtype                      | <class 'numpy.float64'>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| transformation__attribute_1_encoder__handle_unknown             | error                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation__attribute_1_encoder__sparse                     | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__product_code_encoder__categories                | auto                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| transformation__product_code_encoder__drop                      |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| transformation__product_code_encoder__dtype                     | <class 'numpy.float64'>                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        |
| transformation__product_code_encoder__handle_unknown            | error                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          |
| transformation__product_code_encoder__sparse                    | True                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| model__ccp_alpha                                                | 0.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| model__class_weight                                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| model__criterion                                                | gini                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
| model__max_depth                                                | 4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| model__max_features                                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| model__max_leaf_nodes                                           |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| model__min_impurity_decrease                                    | 0.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| model__min_samples_leaf                                         | 1                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| model__min_samples_split                                        | 2                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                              |
| model__min_weight_fraction_leaf                                 | 0.0                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
| model__random_state                                             |                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
| model__splitter                                                 | best                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |

</details>

### Model Plot

The model plot is below.

<style>#sk-cbcf73f3-3df0-460c-a28c-e975797de98c {color: black;background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c pre{padding: 0;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-toggleable {background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c label.sk-toggleable__label-arrow:before {content: "▸";float: left;margin-right: 0.25em;color: #696969;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: "▾";}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-estimator:hover {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item::after {content: "";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-serial::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-item {z-index: 1;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel::before {content: "";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 2em;bottom: 0;left: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item {display: flex;flex-direction: column;position: relative;background-color: white;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-parallel-item:only-child::after {width: 0;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;position: relative;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label label {font-family: monospace;font-weight: bold;background-color: white;display: inline-block;line-height: 1.2em;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-label-container {position: relative;z-index: 2;text-align: center;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-cbcf73f3-3df0-460c-a28c-e975797de98c div.sk-text-repr-fallback {display: none;}</style><div id="sk-cbcf73f3-3df0-460c-a28c-e975797de98c" class="sk-top-container"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;transformation&#x27;,ColumnTransformer(transformers=[(&#x27;loading_missing_value_imputer&#x27;,SimpleImputer(),[&#x27;loading&#x27;]),(&#x27;numerical_missing_value_imputer&#x27;,SimpleImputer(),[&#x27;loading&#x27;, &#x27;measurement_3&#x27;,&#x27;measurement_4&#x27;,&#x27;measurement_5&#x27;,&#x27;measurement_6&#x27;,&#x27;measurement_7&#x27;,&#x27;measurement_8&#x27;,&#x27;measurement_9&#x27;,&#x27;measurement_10&#x27;,&#x27;measurement_11&#x27;,&#x27;measurement_12&#x27;,&#x27;measurement_13&#x27;,&#x27;measurement_14&#x27;,&#x27;measurement_15&#x27;,&#x27;measurement_16&#x27;,&#x27;measurement_17&#x27;]),(&#x27;attribute_0_encoder&#x27;,OneHotEncoder(),[&#x27;attribute_0&#x27;]),(&#x27;attribute_1_encoder&#x27;,OneHotEncoder(),[&#x27;attribute_1&#x27;]),(&#x27;product_code_encoder&#x27;,OneHotEncoder(),[&#x27;product_code&#x27;])])),(&#x27;model&#x27;, DecisionTreeClassifier(max_depth=4))])</pre><b>Please rerun this cell to show the HTML repr or trust the notebook.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="4039f6df-38bb-4617-ac8b-f6e94de8a91c" type="checkbox" ><label for="4039f6df-38bb-4617-ac8b-f6e94de8a91c" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[(&#x27;transformation&#x27;,ColumnTransformer(transformers=[(&#x27;loading_missing_value_imputer&#x27;,SimpleImputer(),[&#x27;loading&#x27;]),(&#x27;numerical_missing_value_imputer&#x27;,SimpleImputer(),[&#x27;loading&#x27;, &#x27;measurement_3&#x27;,&#x27;measurement_4&#x27;,&#x27;measurement_5&#x27;,&#x27;measurement_6&#x27;,&#x27;measurement_7&#x27;,&#x27;measurement_8&#x27;,&#x27;measurement_9&#x27;,&#x27;measurement_10&#x27;,&#x27;measurement_11&#x27;,&#x27;measurement_12&#x27;,&#x27;measurement_13&#x27;,&#x27;measurement_14&#x27;,&#x27;measurement_15&#x27;,&#x27;measurement_16&#x27;,&#x27;measurement_17&#x27;]),(&#x27;attribute_0_encoder&#x27;,OneHotEncoder(),[&#x27;attribute_0&#x27;]),(&#x27;attribute_1_encoder&#x27;,OneHotEncoder(),[&#x27;attribute_1&#x27;]),(&#x27;product_code_encoder&#x27;,OneHotEncoder(),[&#x27;product_code&#x27;])])),(&#x27;model&#x27;, DecisionTreeClassifier(max_depth=4))])</pre></div></div></div><div class="sk-serial"><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="61e07386-e7b7-418a-9af8-41b0261577b4" type="checkbox" ><label for="61e07386-e7b7-418a-9af8-41b0261577b4" class="sk-toggleable__label sk-toggleable__label-arrow">transformation: ColumnTransformer</label><div class="sk-toggleable__content"><pre>ColumnTransformer(transformers=[(&#x27;loading_missing_value_imputer&#x27;,SimpleImputer(), [&#x27;loading&#x27;]),(&#x27;numerical_missing_value_imputer&#x27;,SimpleImputer(),[&#x27;loading&#x27;, &#x27;measurement_3&#x27;, &#x27;measurement_4&#x27;,&#x27;measurement_5&#x27;, &#x27;measurement_6&#x27;,&#x27;measurement_7&#x27;, &#x27;measurement_8&#x27;,&#x27;measurement_9&#x27;, &#x27;measurement_10&#x27;,&#x27;measurement_11&#x27;, &#x27;measurement_12&#x27;,&#x27;measurement_13&#x27;, &#x27;measurement_14&#x27;,&#x27;measurement_15&#x27;, &#x27;measurement_16&#x27;,&#x27;measurement_17&#x27;]),(&#x27;attribute_0_encoder&#x27;, OneHotEncoder(),[&#x27;attribute_0&#x27;]),(&#x27;attribute_1_encoder&#x27;, OneHotEncoder(),[&#x27;attribute_1&#x27;]),(&#x27;product_code_encoder&#x27;, OneHotEncoder(),[&#x27;product_code&#x27;])])</pre></div></div></div><div class="sk-parallel"><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="543953aa-7345-4433-b640-9ebcb9cfaed6" type="checkbox" ><label for="543953aa-7345-4433-b640-9ebcb9cfaed6" class="sk-toggleable__label sk-toggleable__label-arrow">loading_missing_value_imputer</label><div class="sk-toggleable__content"><pre>[&#x27;loading&#x27;]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="28f1b85a-54e9-44db-b914-819af4998fd1" type="checkbox" ><label for="28f1b85a-54e9-44db-b914-819af4998fd1" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer()</pre></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="d8710d93-e747-4796-95d5-77538856cb1d" type="checkbox" ><label for="d8710d93-e747-4796-95d5-77538856cb1d" class="sk-toggleable__label sk-toggleable__label-arrow">numerical_missing_value_imputer</label><div class="sk-toggleable__content"><pre>[&#x27;loading&#x27;, &#x27;measurement_3&#x27;, &#x27;measurement_4&#x27;, &#x27;measurement_5&#x27;, &#x27;measurement_6&#x27;, &#x27;measurement_7&#x27;, &#x27;measurement_8&#x27;, &#x27;measurement_9&#x27;, &#x27;measurement_10&#x27;, &#x27;measurement_11&#x27;, &#x27;measurement_12&#x27;, &#x27;measurement_13&#x27;, &#x27;measurement_14&#x27;, &#x27;measurement_15&#x27;, &#x27;measurement_16&#x27;, &#x27;measurement_17&#x27;]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="b23ea887-b3eb-4dbc-ba26-dd3e0e018c70" type="checkbox" ><label for="b23ea887-b3eb-4dbc-ba26-dd3e0e018c70" class="sk-toggleable__label sk-toggleable__label-arrow">SimpleImputer</label><div class="sk-toggleable__content"><pre>SimpleImputer()</pre></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="c87a37af-e576-4840-bf8c-7e7f5b8ab39e" type="checkbox" ><label for="c87a37af-e576-4840-bf8c-7e7f5b8ab39e" class="sk-toggleable__label sk-toggleable__label-arrow">attribute_0_encoder</label><div class="sk-toggleable__content"><pre>[&#x27;attribute_0&#x27;]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="580ea11e-4df6-4bce-b994-dc4d342d42d4" type="checkbox" ><label for="580ea11e-4df6-4bce-b994-dc4d342d42d4" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="8ccfa95c-d0f7-4dd2-8be2-0885a564d231" type="checkbox" ><label for="8ccfa95c-d0f7-4dd2-8be2-0885a564d231" class="sk-toggleable__label sk-toggleable__label-arrow">attribute_1_encoder</label><div class="sk-toggleable__content"><pre>[&#x27;attribute_1&#x27;]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="e1ed00d2-3cb6-43cd-9ba5-bc0518c93345" type="checkbox" ><label for="e1ed00d2-3cb6-43cd-9ba5-bc0518c93345" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></div></div></div></div></div></div><div class="sk-parallel-item"><div class="sk-item"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="b94ddf76-0075-4efc-9cc4-8c6b69fefad5" type="checkbox" ><label for="b94ddf76-0075-4efc-9cc4-8c6b69fefad5" class="sk-toggleable__label sk-toggleable__label-arrow">product_code_encoder</label><div class="sk-toggleable__content"><pre>[&#x27;product_code&#x27;]</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="1d06bc4d-04b9-44d6-a23f-cdc26d70b7e2" type="checkbox" ><label for="1d06bc4d-04b9-44d6-a23f-cdc26d70b7e2" class="sk-toggleable__label sk-toggleable__label-arrow">OneHotEncoder</label><div class="sk-toggleable__content"><pre>OneHotEncoder()</pre></div></div></div></div></div></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="208c2a51-a582-469b-9bd1-23b9a3968840" type="checkbox" ><label for="208c2a51-a582-469b-9bd1-23b9a3968840" class="sk-toggleable__label sk-toggleable__label-arrow">DecisionTreeClassifier</label><div class="sk-toggleable__content"><pre>DecisionTreeClassifier(max_depth=4)</pre></div></div></div></div></div></div></div>

## Evaluation Results

You can find the details about evaluation process and the evaluation results.



| Metric   |    Value |
|----------|----------|
| accuracy | 0.778564 |
| f1 score | 0.778564 |

# How to Get Started with the Model

Use the code below to get started with the model.

<details>
<summary> Click to expand </summary>

```python
import pickle 
with open(decision-tree-playground-kaggle/model.pkl, 'rb') as file: 
    clf = pickle.load(file)
```

</details>




# Model Card Authors

This model card is written by following authors:

huggingface

# Model Card Contact

You can contact the model card authors through following channels:
[More Information Needed]

# Citation

Below you can find information related to citation.

**BibTeX:**
```
[More Information Needed]
```


Tree Plot
![Tree Plot](decision-tree-playground-kaggle/tree.png)



Confusion Matrix
![Confusion Matrix](decision-tree-playground-kaggle/confusion_matrix.png)