python 기계 학습: 선형 회귀집 값 과 주택 사이즈 관계 의 선형 적합

#     (Linear Regression)            ，
#                             
#    
#     ：    
#     ：
# 1.       sklearn 
# 2.      ，      
# 3.     
import matplotlib.pyplot as plt#  matplotlib pyplot  ，     MATLAB     API
#    sklearn  linear_model        
from sklearn import linear_model
import numpy as np
datasets_x = []
datasets_y = []
fr = open('prices.txt', 'r')
#        
lines = fr.readlines()
#      ，        
for line in lines:
    items = line.strip().split(',')#               
    datasets_x.append(int(items[0]))
    datasets_y.append(int(items[1]))
length = len(datasets_x)
#  datasets_X     ，     ，                 。
datasets_x = np.array(datasets_x).reshape([length,1])
datasets_y = np.array(datasets_y)
minX = min(datasets_x)
maxX = max(datasets_x)
x = np.arange(minX,maxX).reshape([-1,1])
linear = linear_model.LinearRegression()
linear.fit(datasets_x, datasets_y)

plt.scatter(datasets_x,datasets_y,color = 'red')
plt.plot(x, linear.predict(x), color = 'blue')
plt.xlabel('Area')
plt.ylabel('Price')
plt.show()