#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Mar 14 10:46:44 2022

@author: tanu
"""
# Link: https://laptrinhx.com/how-to-run-30-machine-learning-models-with-2-lines-of-code-1521663246/
import pyforest
import warnings
warnings.filterwarnings("ignore")
from sklearn import metrics
from sklearn.metrics import accuracy_score
import lazypredict
from lazypredict.Supervised import LazyClassifier

#%%
target = target1
#target = target3
X_trainN, X_testN, y_trainN, y_testN = train_test_split(numerical_features_df, 
                                                    target, 
                                                    test_size = 0.33, 
                                                    random_state = 42)


#%%
clf = LazyClassifier(verbose=0,ignore_warnings=True)
modelsN, predictionsN = clf.fit(X_trainN, X_testN, y_trainN, y_testN)
mm_lpN = modelsN

#%%
# DOESN't work as need to incorporate pipeline(one hot encoder)
models, predictions = clf.fit(X_train, X_test, y_train, y_test)
mm_lp = models

model1 = Pipeline(steps = [('preprocess', MinMaxScaler())
                                , ('multiModels', clf) ])

models, predictions = model1.fit(X_trainN, X_testN, y_trainN, y_testN)