#
# µû¶óÇÏ¸ç ¹è¿ì´Â ÆÄÀ̽ã°ú µ¥ÀÌÅͰúÇÐ(»ý´ÉÃâÆÇ»ç 2020)
# 14.10 üÁú·®Áö¼ö¿Í ´ç´¢¼öÄ¡´Â ¾î¶² »ó°ü°ü°è°¡ ÀÖÀ»±î, 379ÂÊ
#
from sklearn import datasets
from sklearn import linear_model
import numpy as np
regr = linear_model.LinearRegression()
# ´ç´¢º´ µ¥ÀÌÅÍ ¼¼Æ®¸¦ sklearnÀÇ µ¥ÀÌÅÍÁýÇÕÀ¸·ÎºÎÅÍ ÀоîµéÀδÙ.
diabetes = datasets.load_diabetes()
X = diabetes.data[:, np.newaxis, 2]
regr.fit(X, diabetes.target) # ÇнÀÀ» ÅëÇÑ ¼±Çüȸ±Í ¸ðµ¨À» »ý¼º
print(regr.coef_, regr.intercept_)