本文整理汇总了Python中sklearn.decomposition.IncrementalPCA.get_params方法的典型用法代码示例。如果您正苦于以下问题：Python IncrementalPCA.get_params方法的具体用法？Python IncrementalPCA.get_params怎么用？Python IncrementalPCA.get_params使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sklearn.decomposition.IncrementalPCA的用法示例。
在下文中一共展示了IncrementalPCA.get_params方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: print
# 需要导入模块: from sklearn.decomposition import IncrementalPCA [as 别名]
# 或者: from sklearn.decomposition.IncrementalPCA import get_params [as 别名]
print('#================================================================#')
print('\nshape of Training Matrix = ', Train_matrix.shape)
print('shape of Test Matrix = ', Test_matrix.shape,'\n')
print('#================================================================#')
#========================= Principal Component Analysis ==========================#
print ('\nRunning Incrmental PCA with 200 Componenets and 5000 batch size')
pca = IncrementalPCA(n_components=200, batch_size = 5000)
pca.fit(Train_matrix)
Train_matrix = pca.transform(Train_matrix)
Test_matrix = pca.transform(Test_matrix)
parameters = pca.get_params()
variance = pca.explained_variance_ratio_
cumvariance = pca.explained_variance_ratio_.cumsum()
#np.savetxt("pca_result_variance_200.csv", variance, delimiter=",")
#np.savetxt("pca_result_cum_variance_200.csv", variance, delimiter=",")
print ('\nPCA complete!\n')
print ('#================================================================#')
print('\nWriting transformed Train and Test matrices to CSV\n')
print('#================================================================#')
with open(csv_pca_train_out_path, 'w', newline='') as csvtrainoutfile:
csv_matrix_writer(csvtrainoutfile , Train_matrix)
with open(csv_pca_test_out_path, 'w', newline='') as csvtestoutfile:
csv_matrix_writer(csvtestoutfile , Test_matrix)