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adrian-lam
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ubcv-grade-predictor-ridge

Tabular Regression
Scikit-learn
Joblib
skops
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Model description

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Intended uses & limitations

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Training Procedure

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Hyperparameters

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Hyperparameter Value
memory
steps [('columntransformer', ColumnTransformer(transformers=[('pipeline-1',
Pipeline(steps=[('simpleimputer',
SimpleImputer()),
('standardscaler',
StandardScaler())]),
['Course_Avg_Roll_1y', 'Course_Min_Last_3y',
'Course_Max_Last_3y', 'Course_Std_Last_3y']),
('pipeline-2',
Pipeline(steps=[('simpleimputer',
SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_b...
SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]),
['CourseLevel', 'Years_Since_Start',
'Prof_Courses_Taught', 'Year']),
('drop', 'drop',
['Reported', 'Section', 'Detail', 'Median',
'Percentile (25)', 'Percentile (75)', 'High',
'Low', '<50', '50-54', '55-59', '60-63',
'64-67', '68-71', '72-75', '76-79', '80-84',
'85-89', '90-100'])])), ('ridge', Ridge(alpha=2.091, random_state=42))]
transform_input
verbose False
columntransformer ColumnTransformer(transformers=[('pipeline-1',
Pipeline(steps=[('simpleimputer',
SimpleImputer()),
('standardscaler',
StandardScaler())]),
['Course_Avg_Roll_1y', 'Course_Min_Last_3y',
'Course_Max_Last_3y', 'Course_Std_Last_3y']),
('pipeline-2',
Pipeline(steps=[('simpleimputer',
SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_b...
SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]),
['CourseLevel', 'Years_Since_Start',
'Prof_Courses_Taught', 'Year']),
('drop', 'drop',
['Reported', 'Section', 'Detail', 'Median',
'Percentile (25)', 'Percentile (75)', 'High',
'Low', '<50', '50-54', '55-59', '60-63',
'64-67', '68-71', '72-75', '76-79', '80-84',
'85-89', '90-100'])])
ridge Ridge(alpha=2.091, random_state=42)
columntransformer__force_int_remainder_cols True
columntransformer__n_jobs
columntransformer__remainder drop
columntransformer__sparse_threshold 0.3
columntransformer__transformer_weights
columntransformer__transformers [('pipeline-1', Pipeline(steps=[('simpleimputer', SimpleImputer()),
('standardscaler', StandardScaler())]), ['Course_Avg_Roll_1y', 'Course_Min_Last_3y', 'Course_Max_Last_3y', 'Course_Std_Last_3y']), ('pipeline-2', Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_binary', handle_unknown='ignore'))]), ['Campus', 'Session', 'SubjectCourse', 'Professor', 'Subject']), ('pipeline-3', Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))]), ['CourseLevel', 'Years_Since_Start', 'Prof_Courses_Taught', 'Year']), ('drop', 'drop', ['Reported', 'Section', 'Detail', 'Median', 'Percentile (25)', 'Percentile (75)', 'High', 'Low', '<50', '50-54', '55-59', '60-63', '64-67', '68-71', '72-75', '76-79', '80-84', '85-89', '90-100'])]
columntransformer__verbose False
columntransformer__verbose_feature_names_out True
columntransformer__pipeline-1 Pipeline(steps=[('simpleimputer', SimpleImputer()),
('standardscaler', StandardScaler())])
columntransformer__pipeline-2 Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('onehotencoder',
OneHotEncoder(drop='if_binary', handle_unknown='ignore'))])
columntransformer__pipeline-3 Pipeline(steps=[('simpleimputer', SimpleImputer(strategy='most_frequent')),
('ordinalencoder',
OrdinalEncoder(handle_unknown='use_encoded_value',
unknown_value=-1))])
columntransformer__drop drop
columntransformer__pipeline-1__memory
columntransformer__pipeline-1__steps [('simpleimputer', SimpleImputer()), ('standardscaler', StandardScaler())]
columntransformer__pipeline-1__transform_input
columntransformer__pipeline-1__verbose False
columntransformer__pipeline-1__simpleimputer SimpleImputer()
columntransformer__pipeline-1__standardscaler StandardScaler()
columntransformer__pipeline-1__simpleimputer__add_indicator False
columntransformer__pipeline-1__simpleimputer__copy True
columntransformer__pipeline-1__simpleimputer__fill_value
columntransformer__pipeline-1__simpleimputer__keep_empty_features False
columntransformer__pipeline-1__simpleimputer__missing_values nan
columntransformer__pipeline-1__simpleimputer__strategy mean
columntransformer__pipeline-1__standardscaler__copy True
columntransformer__pipeline-1__standardscaler__with_mean True
columntransformer__pipeline-1__standardscaler__with_std True
columntransformer__pipeline-2__memory
columntransformer__pipeline-2__steps [('simpleimputer', SimpleImputer(strategy='most_frequent')), ('onehotencoder', OneHotEncoder(drop='if_binary', handle_unknown='ignore'))]
columntransformer__pipeline-2__transform_input
columntransformer__pipeline-2__verbose False
columntransformer__pipeline-2__simpleimputer SimpleImputer(strategy='most_frequent')
columntransformer__pipeline-2__onehotencoder OneHotEncoder(drop='if_binary', handle_unknown='ignore')
columntransformer__pipeline-2__simpleimputer__add_indicator False
columntransformer__pipeline-2__simpleimputer__copy True
columntransformer__pipeline-2__simpleimputer__fill_value
columntransformer__pipeline-2__simpleimputer__keep_empty_features False
columntransformer__pipeline-2__simpleimputer__missing_values nan
columntransformer__pipeline-2__simpleimputer__strategy most_frequent
columntransformer__pipeline-2__onehotencoder__categories auto
columntransformer__pipeline-2__onehotencoder__drop if_binary
columntransformer__pipeline-2__onehotencoder__dtype <class 'numpy.float64'>
columntransformer__pipeline-2__onehotencoder__feature_name_combiner concat
columntransformer__pipeline-2__onehotencoder__handle_unknown ignore
columntransformer__pipeline-2__onehotencoder__max_categories
columntransformer__pipeline-2__onehotencoder__min_frequency
columntransformer__pipeline-2__onehotencoder__sparse_output True
columntransformer__pipeline-3__memory
columntransformer__pipeline-3__steps [('simpleimputer', SimpleImputer(strategy='most_frequent')), ('ordinalencoder', OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1))]
columntransformer__pipeline-3__transform_input
columntransformer__pipeline-3__verbose False
columntransformer__pipeline-3__simpleimputer SimpleImputer(strategy='most_frequent')
columntransformer__pipeline-3__ordinalencoder OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-1)
columntransformer__pipeline-3__simpleimputer__add_indicator False
columntransformer__pipeline-3__simpleimputer__copy True
columntransformer__pipeline-3__simpleimputer__fill_value
columntransformer__pipeline-3__simpleimputer__keep_empty_features False
columntransformer__pipeline-3__simpleimputer__missing_values nan
columntransformer__pipeline-3__simpleimputer__strategy most_frequent
columntransformer__pipeline-3__ordinalencoder__categories auto
columntransformer__pipeline-3__ordinalencoder__dtype <class 'numpy.float64'>
columntransformer__pipeline-3__ordinalencoder__encoded_missing_value nan
columntransformer__pipeline-3__ordinalencoder__handle_unknown use_encoded_value
columntransformer__pipeline-3__ordinalencoder__max_categories
columntransformer__pipeline-3__ordinalencoder__min_frequency
columntransformer__pipeline-3__ordinalencoder__unknown_value -1
ridge__alpha 2.091
ridge__copy_X True
ridge__fit_intercept True
ridge__max_iter
ridge__positive False
ridge__random_state 42
ridge__solver auto
ridge__tol 0.0001

Model Plot 

Pipeline(steps=[('columntransformer',ColumnTransformer(transformers=[('pipeline-1',Pipeline(steps=[('simpleimputer',SimpleImputer()),('standardscaler',StandardScaler())]),['Course_Avg_Roll_1y','Course_Min_Last_3y','Course_Max_Last_3y','Course_Std_Last_3y']),('pipeline-2',Pipeline(steps=[('simpleimputer',SimpleImputer(strategy='most_frequent')),('on...OrdinalEncoder(handle_unknown='use_encoded_value',unknown_value=-1))]),['CourseLevel','Years_Since_Start','Prof_Courses_Taught','Year']),('drop', 'drop',['Reported', 'Section','Detail', 'Median','Percentile (25)','Percentile (75)', 'High','Low', '<50', '50-54','55-59', '60-63', '64-67','68-71', '72-75', '76-79','80-84', '85-89','90-100'])])),('ridge', Ridge(alpha=2.091, random_state=42))])
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