筑波大学の機械学習講座：課題のPythonスクリプト部分を作りながらsklearnを勉強する (2) - Qiita

import pandas as pd import numpy as np import matplotlib.pyplot as plt import copy from sklearn.preprocessing import PolynomialFeatures as PF from sklearn import linear_model from sklearn.metrics import mean_squared_error # 訓練用データの数 NUM_TR = 6 np.random.seed(0) rng = np.random.RandomState(0) # 描画用のx軸データ x_plot = np.linspace(0,10,100) # 訓練データ tmp = copy.deepcopy(x_plot) rng.shuffle(tmp) x_tr = np.s