| 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")) |