# default imports
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeRegressor
from sklearn.metrics import mean_squared_error
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
plt.switch_backend('agg')

data = pd.read_csv("./data/house_pricing.csv")
X = data.iloc[:, :-1]
y = data.iloc[:, -1]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9)

depth_list = [2, 8, 10, 15, 20, 25, 30, 35, 45, 50, 80]

# Write your solution here :
