2.4　參考文獻及網頁鏈接

[1] 2.2. Manifold learning?. 2.2. Manifold learning — scikit-learn 0.19.0 documentation. Available at: http://scikit-learn.org/stable/modules/manifold.html.

[2] Cross entropy. Wikipedia (2017). Available at: https://en.wikipedia.org/wiki/Cross_entropy.

[3] Foundation, N. I. P. S. NIPS 2017. Available at: https://nips.cc/Conferences/2016/Schedule?showEvent=6203.

[4] Logistic regression. Wikipedia (2017). Available at: https://en.wikipedia.org/wiki/ Logistic_regression.

[5] One Hot Encoding in Scikit-Learn. ritchieng.github.io. Available at: http://www.ritchieng.com/ machinelearning-one-hot-encoding/.

[6] Training, test and validation sets. Wikipedia (2017). Available at: http://en.wikipedia.org/wiki/Training,_test_and_validation_sets.

[7] Underfitting vs. Overfitting. Underfitting vs. Overfitting — scikit-learn 0.19.0 documentation. Available at: http://scikit-learn.org/stable/auto_examples/model_selection/plot_underfitting_overfitting.html.

[8] 吳軍．數據之美[M]．2版．北京：人民郵電出版社，2014．

[9] 周志華．機器學習[M]．北京：清華大學出版社，2016．

[10] 機器學習基礎——PCA（主成分分析）．g11d111的博客——CSDN博客．Available at: http://blog.csdn.net/g11d111/article/details/66473643.