In [25]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
In [26]:
np.set_printoptions(precision=3, suppress=True)
In [27]:
dataset = pd.read_csv('Position_Salaries.csv')
In [28]:
X = dataset.iloc[:, 1:2].values
y = dataset.iloc[:, 2].values
In [29]:
from sklearn.tree import DecisionTreeRegressor
In [30]:
regressor = DecisionTreeRegressor(random_state=0)
regressor.fit(X, y)
Out[30]:
In [31]:
regressor.predict(6.5)
Out[31]:
In [32]:
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('Truth or Bluff (Decision Tree Regression)')
plt.xlabel('Position level')
plt.ylabel('Salary')
plt.show()