import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
# Veri setimiz
dataset = pd.read_csv('maas.csv')
X = dataset.iloc[:,1:2].values
y = dataset.iloc[:,2].values
from sklearn.tree import DecisionTreeRegressor
regressor = DecisionTreeRegressor(random_state = 0)
regressor.fit(X,y)
DecisionTreeRegressor(criterion='mse', max_depth=None, max_features=None, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, presort=False, random_state=0, splitter='best')
# Decision Tree Regression sonuçlarını görselleştirme
X_grid = np.arange(min(X), max(X), 0.01)
X_grid = X_grid.reshape((len(X_grid), 1))
plt.scatter(X, y, color = 'red')
plt.plot(X_grid, regressor.predict(X_grid), color = 'blue')
plt.title('Decision Tree Regression')
plt.xlabel('Pozisyon')
plt.ylabel('Maas')
plt.show()
Grafiktende tahmin edileceği gibi seviyesi 7 olan bir kişinin maası 200000 olacaktır.
print(regressor.predict(7))
[ 200000.]
print(regressor.predict(8))
[ 300000.]
print(regressor.predict(9))
[ 500000.]