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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+MiningProcess_Flotation_Plant_Database.csv filter=lfs diff=lfs merge=lfs -text

MiningProcess_Flotation_Plant_Database.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ae0231a0bd2e14aac39cf978d81db6c71907a42aade19327816692c4e30cb956
+size 183766261

Silisyum.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5a555a6a6c7d5c4a3f80ba437b9dbcdc817f84c8c0085ec73ccca7f7c849c5ab
+size 627483

app.py

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+import pandas as pd
+import streamlit as st
+import joblib
+
+from sklearn.preprocessing import StandardScaler, OneHotEncoder
+from sklearn.model_selection import train_test_split
+from sklearn.compose import ColumnTransformer
+
+# Veriyi yükleme ve sütun isimlerini güncelleme
+df = pd.read_csv('MiningProcess_Flotation_Plant_Database.csv')
+df.columns = df.columns.str.replace(r'[\s\.]', '_', regex=True)
+df.columns = df.columns.str.replace(r'%_Silica_Feed', 'Silica_Feed', regex=True)
+df.columns = df.columns.str.replace(r'%_Silica_Concentrate', 'Silica_Concentrate', regex=True)
+columns_to_convert = df.columns.difference(['date'])
+df[columns_to_convert] = df[columns_to_convert].replace(',', '.', regex=True).astype(float)
+
+
+# Bağımlı ve bağımsız değişkenlerin seçimi
+x = df.drop(['date','%_Iron_Feed','%_Iron_Concentrate', 'Silica_Concentrate'], axis=1)
+y = df[['Silica_Concentrate']]
+
+# Eğitim ve test verilerini ayırma
+x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.20, random_state=42)
+
+# Ön işleme (StandardScaler ve OneHotEncoder)
+preprocessor = ColumnTransformer(
+    transformers=[
+        ('num', StandardScaler(), ['Silica_Feed','Starch_Flow','Amina_Flow','Ore_Pulp_Flow','Ore_Pulp_pH','Ore_Pulp_Density',
+                                   'Flotation_Column_01_Air_Flow','Flotation_Column_02_Air_Flow','Flotation_Column_03_Air_Flow',
+                                   'Flotation_Column_04_Air_Flow','Flotation_Column_05_Air_Flow','Flotation_Column_06_Air_Flow',
+                                   'Flotation_Column_07_Air_Flow','Flotation_Column_01_Level','Flotation_Column_02_Level',
+                                   'Flotation_Column_03_Level','Flotation_Column_04_Level','Flotation_Column_05_Level',
+                                   'Flotation_Column_06_Level','Flotation_Column_07_Level'])
+    ]
+)
+
+def silica_pred(Silica_Feed,Starch_Flow,Amina_Flow,Ore_Pulp_Flow,Ore_Pulp_pH,Ore_Pulp_Density,Flotation_Column_01_Air_Flow,
+               Flotation_Column_02_Air_Flow,Flotation_Column_03_Air_Flow,Flotation_Column_04_Air_Flow,Flotation_Column_05_Air_Flow,
+               Flotation_Column_06_Air_Flow,Flotation_Column_07_Air_Flow,Flotation_Column_01_Level,Flotation_Column_02_Level,
+               Flotation_Column_03_Level,Flotation_Column_04_Level,Flotation_Column_05_Level,Flotation_Column_06_Level,	
+               Flotation_Column_07_Level):
+    input_data = pd.DataFrame({
+        'Silica_Feed': [Silica_Feed],
+        'Starch_Flow': [Starch_Flow],
+        'Amina_Flow': [Amina_Flow],
+        'Ore_Pulp_Flow': [Ore_Pulp_Flow],
+        'Ore_Pulp_pH': [Ore_Pulp_pH],
+        'Ore_Pulp_Density': [Ore_Pulp_Density],
+        'Flotation_Column_01_Air_Flow': [Flotation_Column_01_Air_Flow],
+        'Flotation_Column_02_Air_Flow': [Flotation_Column_02_Air_Flow],
+        'Flotation_Column_03_Air_Flow': [Flotation_Column_03_Air_Flow],
+        'Flotation_Column_04_Air_Flow': [Flotation_Column_04_Air_Flow],
+        'Flotation_Column_05_Air_Flow': [Flotation_Column_05_Air_Flow],
+        'Flotation_Column_06_Air_Flow': [Flotation_Column_06_Air_Flow],
+        'Flotation_Column_07_Air_Flow': [Flotation_Column_07_Air_Flow],
+        'Flotation_Column_01_Level': [Flotation_Column_01_Level],
+        'Flotation_Column_02_Level': [Flotation_Column_02_Level],
+        'Flotation_Column_03_Level': [Flotation_Column_03_Level],
+        'Flotation_Column_04_Level': [Flotation_Column_04_Level],
+        'Flotation_Column_05_Level': [Flotation_Column_05_Level],
+        'Flotation_Column_06_Level': [Flotation_Column_06_Level],
+        'Flotation_Column_07_Level': [Flotation_Column_07_Level]
+    })
+    input_data_transformed = preprocessor.fit_transform(input_data)
+
+    model = joblib.load('Silisyum.pkl')
+
+    prediction = model.predict(input_data_transformed)
+    return float(prediction[0])
+
+min_Silica_Feed = x['Silica_Feed'].min()
+max_Silica_Feed = x['Silica_Feed'].max()
+min_Starch_Flow = x['Starch_Flow'].min()
+max_Starch_Flow = x['Starch_Flow'].max()
+min_Amina_Flow = x['Amina_Flow'].min()
+max_Amina_Flow = x['Amina_Flow'].max()
+min_Ore_Pulp_Flow = x['Ore_Pulp_Flow'].min()
+max_Ore_Pulp_Flow = x['Ore_Pulp_Flow'].max()
+min_Ore_Pulp_pH = x['Ore_Pulp_pH'].min()
+max_Ore_Pulp_pH = x['Ore_Pulp_pH'].max()
+min_Ore_Pulp_Density = x['Ore_Pulp_Density'].min()
+max_Ore_Pulp_Density = x['Ore_Pulp_Density'].max()
+min_Flotation_Column_01_Air_Flow = x['Flotation_Column_01_Air_Flow'].min()
+max_Flotation_Column_01_Air_Flow = x['Flotation_Column_01_Air_Flow'].max()
+min_Flotation_Column_02_Air_Flow = x['Flotation_Column_02_Air_Flow'].min()
+max_Flotation_Column_02_Air_Flow = x['Flotation_Column_02_Air_Flow'].max()
+min_Flotation_Column_03_Air_Flow = x['Flotation_Column_03_Air_Flow'].min()
+max_Flotation_Column_03_Air_Flow = x['Flotation_Column_03_Air_Flow'].max()
+min_Flotation_Column_04_Air_Flow = x['Flotation_Column_04_Air_Flow'].min()
+max_Flotation_Column_04_Air_Flow = x['Flotation_Column_04_Air_Flow'].max()
+min_Flotation_Column_05_Air_Flow = x['Flotation_Column_05_Air_Flow'].min()
+max_Flotation_Column_05_Air_Flow = x['Flotation_Column_05_Air_Flow'].max()
+min_Flotation_Column_06_Air_Flow = x['Flotation_Column_06_Air_Flow'].min()
+max_Flotation_Column_06_Air_Flow = x['Flotation_Column_06_Air_Flow'].max()
+min_Flotation_Column_07_Air_Flow = x['Flotation_Column_07_Air_Flow'].min()
+max_Flotation_Column_07_Air_Flow = x['Flotation_Column_07_Air_Flow'].max()
+min_Flotation_Column_01_Level = x['Flotation_Column_01_Level'].min()
+max_Flotation_Column_01_Level = x['Flotation_Column_01_Level'].max()
+min_Flotation_Column_02_Level = x['Flotation_Column_02_Level'].min()
+max_Flotation_Column_02_Level = x['Flotation_Column_02_Level'].max()
+min_Flotation_Column_03_Level = x['Flotation_Column_03_Level'].min()
+max_Flotation_Column_03_Level = x['Flotation_Column_03_Level'].max()
+min_Flotation_Column_04_Level = x['Flotation_Column_04_Level'].min()
+max_Flotation_Column_04_Level = x['Flotation_Column_04_Level'].max()
+min_Flotation_Column_05_Level = x['Flotation_Column_05_Level'].min()
+max_Flotation_Column_05_Level = x['Flotation_Column_05_Level'].max()
+min_Flotation_Column_06_Level = x['Flotation_Column_06_Level'].min()
+max_Flotation_Column_06_Level = x['Flotation_Column_06_Level'].max()
+min_Flotation_Column_07_Level = x['Flotation_Column_07_Level'].min()
+max_Flotation_Column_07_Level = x['Flotation_Column_07_Level'].max()
+
+st.title("Maden Veri seti ile Silica saflık Regresyon Modeli")
+st.write("Veri Gir")
+    
+Silica_Feed = st.slider('Silica_Feed', float(min_Silica_Feed), float(max_Silica_Feed))
+Starch_Flow = st.slider('Starch_Flow', float(min_Starch_Flow), float(max_Starch_Flow))
+Amina_Flow = st.slider('Amina_Flow', float(min_Amina_Flow), float(max_Amina_Flow))
+Ore_Pulp_Flow = st.slider('Ore_Pulp_Flow', float(min_Ore_Pulp_Flow), float(max_Ore_Pulp_Flow))
+Ore_Pulp_pH = st.slider('Ore_Pulp_pH', float(min_Ore_Pulp_pH), float(max_Ore_Pulp_pH))
+Ore_Pulp_Density = st.slider('Ore_Pulp_Density', float(min_Ore_Pulp_Density), float(max_Ore_Pulp_Density))
+Flotation_Column_01_Air_Flow = st.slider('Flotation_Column_01_Air_Flow', float(min_Flotation_Column_01_Air_Flow), float(max_Flotation_Column_01_Air_Flow))
+Flotation_Column_02_Air_Flow = st.slider('Flotation_Column_02_Air_Flow', float(min_Flotation_Column_02_Air_Flow), float(max_Flotation_Column_02_Air_Flow))
+Flotation_Column_03_Air_Flow = st.slider('Flotation_Column_03_Air_Flow', float(min_Flotation_Column_03_Air_Flow), float(max_Flotation_Column_03_Air_Flow))
+Flotation_Column_04_Air_Flow = st.slider('Flotation_Column_04_Air_Flow', float(min_Flotation_Column_04_Air_Flow), float(max_Flotation_Column_04_Air_Flow))
+Flotation_Column_05_Air_Flow = st.slider('Flotation_Column_05_Air_Flow', float(min_Flotation_Column_05_Air_Flow), float(max_Flotation_Column_05_Air_Flow))
+Flotation_Column_06_Air_Flow = st.slider('Flotation_Column_06_Air_Flow', float(min_Flotation_Column_06_Air_Flow), float(max_Flotation_Column_06_Air_Flow))
+Flotation_Column_07_Air_Flow = st.slider('Flotation_Column_07_Air_Flow', float(min_Flotation_Column_07_Air_Flow), float(max_Flotation_Column_07_Air_Flow))
+Flotation_Column_01_Level = st.slider('Flotation_Column_01_Level', float(min_Flotation_Column_01_Level), float(max_Flotation_Column_01_Level))
+Flotation_Column_02_Level = st.slider('Flotation_Column_02_Level', float(min_Flotation_Column_02_Level), float(max_Flotation_Column_02_Level))
+Flotation_Column_03_Level = st.slider('Flotation_Column_03_Level', float(min_Flotation_Column_03_Level), float(max_Flotation_Column_03_Level))
+Flotation_Column_04_Level = st.slider('Flotation_Column_04_Level', float(min_Flotation_Column_04_Level), float(max_Flotation_Column_04_Level))
+Flotation_Column_05_Level = st.slider('Flotation_Column_05_Level', float(min_Flotation_Column_05_Level), float(max_Flotation_Column_05_Level))
+Flotation_Column_06_Level = st.slider('Flotation_Column_06_Level', float(min_Flotation_Column_06_Level), float(max_Flotation_Column_06_Level))
+Flotation_Column_07_Level = st.slider('Flotation_Column_07_Level', float(min_Flotation_Column_07_Level), float(max_Flotation_Column_07_Level))
+
+
+# Predict button
+if st.button('Silica Saflığını Tahmin Et'):
+    prediction = silica_pred(Silica_Feed, Starch_Flow, Amina_Flow, Ore_Pulp_Flow, Ore_Pulp_pH, Ore_Pulp_Density, 
+                                Flotation_Column_01_Air_Flow, Flotation_Column_02_Air_Flow, Flotation_Column_03_Air_Flow, 
+                                Flotation_Column_04_Air_Flow, Flotation_Column_05_Air_Flow, Flotation_Column_06_Air_Flow, 
+                                Flotation_Column_07_Air_Flow, Flotation_Column_01_Level, Flotation_Column_02_Level, 
+                                Flotation_Column_03_Level, Flotation_Column_04_Level, Flotation_Column_05_Level, 
+                                Flotation_Column_06_Level, Flotation_Column_07_Level)
+        
+    st.write(f'Tahmin edilen Silica Saflığı: {prediction:.2f}')

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+scikit-learn
+pandas
+tensorflow