偏差-方差均衡原理

作者：金良（[email protected]） csdn博客： http://blog.csdn.net/u012176591

* Bias–variance tradeoff
http://en.wikipedia.org/wiki/Bias%E2%80%93variance_tradeoff
* 机器学习中的数学(2)-线性回归，偏差、方差权衡
http://www.cnblogs.com/LeftNotEasy/archive/2010/12/19/mathmatic_in_machine_learning_2_regression_and_bias_variance_trade_off.html
* Understanding the Bias-Variance Tradeoff
http://scott.fortmann-roe.com/docs/BiasVariance.html
* Accurately Measuring Model Prediction Error
http://scott.fortmann-roe.com/docs/MeasuringError.html
* 交叉验证
http://blog.sciencenet.cn/blog-397960-666113.html
* 交叉验证——维基百科
http://zh.wikipedia.org/wiki/%E4%BA%A4%E5%8F%89%E9%A9%97%E8%AD%89
http://en.wikipedia.org/wiki/Cross-validation_%28statistics%29
* 文本分类入门（十）特征选择算法之开方检验
http://www.blogjava.net/zhenandaci/archive/2014/11/05/225966.html#419523
里面有个“假设检验”思想，了解一下
有个问题：互信息和信息增益不是一回事么？
* Cross-validation pitfalls when selecting and assessing regression and classification models
http://www.jcheminf.com/content/pdf/1758-2946-6-10.pdf
* A study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
http://www.cs.iastate.edu/~jtian/cs573/Papers/Kohavi-IJCAI-95.pdf
* Cross Validation
http://www.cs.cmu.edu/~schneide/tut5/node42.html
* cross-validation for detecting and preventing overfitting
http://www.autonlab.org/tutorials/overfit10.pdf
* Differences between L1 and L2 as Loss Function and Regularization
http://www.chioka.in/differences-between-l1-and-l2-as-loss-function-and-regularization/