text_plain_output_1.png
import os

import numpy as np
import pandas as pd
from sklearn.model_selection import cross_val_score, cross_val_predict, StratifiedKFold
import seaborn as sns
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn import linear_model, svm
from sklearn.ensemble import GradientBoostingRegressor as xgb
from sklearn.metrics import confusion_matrix, accuracy_score, f1_score
from scipy import stats
import seaborn as sns
from sklearn.impute import SimpleImputer
from sklearn import linear_model, svm
import datetime
from sklearn.model_selection import KFold
from sklearn.model_selection import train_test_split
import time
from sklearn import preprocessing
from scipy.stats import skew
import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))