regression best random_state
#x->independent variable #y->dependent variable #model->algorithm def maxr2_score(model,x,y): max_r_score=0 for r_state in range(42,101): x_train,x_test,y_train,y_test=train_test_split(x,y,random_state=r_state) model.fit(x_train,y_train) pred=model.predict(x_test) score=r2_score(y_test,pred) if score>max_r_score: max_r_score=score final_r_state=r_state print('max_r2_score is at random_state ',final_r_state,' which is ',max_r_score) return final_r_state
