1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # # µû¶óÇÏ¸ç ¹è¿ì´Â ÆÄÀ̽ã°ú µ¥ÀÌÅͰúÇÐ(»ý´ÉÃâÆÇ»ç 2020) # 14.9 »çÀÌŶ·±ÀÇ ´ç´¢º´ ¿¹Á¦¿Í ÇнÀ µ¥ÀÌÅÍ »ý¼º, 377ÂÊ # import matplotlib.pyplot as plt import numpy as np from sklearn.linear_model import LinearRegression from sklearn import datasets # ´ç´¢º´ µ¥ÀÌÅÍ ¼¼Æ®¸¦ sklearnÀÇ µ¥ÀÌÅÍÁýÇÕÀ¸·ÎºÎÅÍ ÀоîµéÀδÙ. diabetes = datasets.load_diabetes() print('shape of diabetes.data: ', diabetes.data.shape) print(diabetes.data) print('ÀԷµ¥ÀÌÅÍÀÇ Æ¯¼ºµé') print(diabetes.feature_names) print('target data y:', diabetes.target.shape) print(diabetes.target) X = diabetes.data[:, np.newaxis, 2] # ¹è¿ÀÇ Â÷¿øÀ» Áõ°¡½ÃÅ´ print(X) # (442, 1) ÇüÅÂÀÇ Çà·ÄÀÌ µÇ¾ú´Â°¡ È®ÀÎ | cs |