text_plain_output_1.png
import os

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.preprocessing import OrdinalEncoder
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import OneHotEncoder
from sklearn.ensemble import RandomForestRegressor
from sklearn.metrics import mean_squared_error
from category_encoders import MEstimateEncoder
from sklearn.cluster import KMeans
from sklearn.decomposition import PCA
from sklearn.feature_selection import mutual_info_regression
from sklearn.model_selection import KFold, cross_val_score
from xgboost import XGBRegressor
import os
for dirname, _, filenames in os.walk('/kaggle/input'):
    for filename in filenames:
        print(os.path.join(dirname, filename))