Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""Untitled0.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1TrLYru7HIkMCSYavUVhf6DZ-5lYqp3zI
+"""
+
+import pandas as pd
+import numpy as np
+from sklearn.pipeline import Pipeline
+from sklearn.compose import ColumnTransformer
+from sklearn.preprocessing import  StandardScaler
+from sklearn.tree import DecisionTreeClassifier
+
+df=pd.read_csv('wine_red.csv')
+df.drop(['residual_sugar','pH','free_sulfur_dioxide'],axis=1,inplace=True)
+X_train = df.drop('quality',axis=1)
+y_train = df.pop("quality")
+
+num_col = X_train.select_dtypes(include=['int64', 'float64']).columns
+preprocessor = ColumnTransformer([("scaler", StandardScaler(), num_col)])
+num_col = X_train.select_dtypes(include=['int64', 'float64']).columns
+preprocessor = ColumnTransformer([("scaler", StandardScaler(), num_col)])
+model = Pipeline(steps=[('preprocessor', preprocessor), ('decisiontree', DecisionTreeClassifier())]) 
+model.fit(X_train, y_train)
+
+model = Pipeline(steps=[('scaler', StandardScaler()), 
+                ('decisiontree', DecisionTreeClassifier())])
+
+model.fit(X_train, y_train)
+
+"""### Saving the model"""
+
+import joblib
+
+joblib.dump(model,'model.joblib')