Create model.py

model.py

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+import pandas as pd
+import numpy as np
+from sklearn.model_selection import train_test_split
+from sklearn.tree import DecisionTreeClassifier
+import pickle
+
+df = pd.read_csv('Clean_cancer_dataset.csv')
+
+x = df.drop(['diagnosis','Unnamed: 0'],axis=1)
+y = df['diagnosis']
+
+x_train , x_test , y_train , y_test = train_test_split(x,y,test_size=0.2,random_state=908)
+
+model = DecisionTreeClassifier()
+model.fit(x_train,y_train)
+
+pickle.dump(model,open("model.pkl","wb"))