# 导入库
import pandas as pd
import numpy as np

# 导入数据集
dataset = pd.read_csv('dataset/50_Startups.csv')
X = dataset.iloc[:, :-1].values
Y = dataset.iloc[:, 4].values

# 类别数据数字化
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
labelEncoder = LabelEncoder()
X[:, 3] = labelEncoder.fit_transform(X[:, 3])
onehotencoder = OneHotEncoder(categorical_features = [3])
X = onehotencoder.fit_transform(X).toarray()

# 躲避虚拟变量陷阱
X = X[:, 1:]

# 拆分数据集
from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.2, random_state = 0)

# 训练
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, Y_train)

y_pred = regressor.predict(X_test);

print(y_pred)