print('the mean sqare error:%.2f' %np.mean((regr.predict(diabetes_X_test)-diabetes_y_test)**2)) print('Variance score:%.2f' %regr.score(diabetes_X_test,diabetes_y_test)) ##散点图 plt.scatter(diabetes_X_test,diabetes_y_test,color='black') plt.plot(diabetes_X_test,regr.predict(...
Line Regression Example DataBase:diavetes """ import matplotlib.pyplot as plt import numpy as np from sklearn import datasets,linear_model import time a=time.time() ###加载数据集 diabetes=datasets.load_diabetes() ###仅仅使用一个特征: diabetes_X=diabetes.data[:,np.newaxis,2] ###s数据划分...
点击详细解释: 90% Line (90 th Percentile) is the value below which 90% of the samples fall. The remaining samples too at least as long as the value. This is a standard statistical measure. See, for example: Percentile entry at Wikipedia. 百分位数: 统计学术语,如果将一组数据从大到小排序...
prediction_variance_degree2.py robust_regression.py run_opt_to_find_best_number_of_line_segments.py sinWaveFit.png sinWaveFit16.png sineWave.py sineWave_custom_opt_bounds.py sineWave_degrees.py sineWave_time_compare.py slope_constraint_demo.ipynb ...
Depicted are the first two principal components, explaining > 75% of the variance in the data. Data was power-transformed and standardized before the analysis. B Pair-plot, depicting the pairwise Spearman correlation between each pair of samples, and a histogram of normalized gene expression...
The scatter plot below shows the result of price prediction for parts of house with model. Each point on x-axis represents the median of the real price of the same type of house, and the y-axis represents the result of the linear regression model based on the feature prediction. When ...