Machine learning and bioinformaticss

ML and bioinformatics.

SungRoh Yoon

ACM-BCB 2016 Tutorial

Deep learning for Bioinformatics and Healt Informatics

Convoloutional neuralnetworks

RNN (recurrent neuroanl network)

PRML 经典书用来学习基础

比较计算的讲法

Christopher M Bishop作者.

还有一种比较统计的讲法.

统计分两个学派:频率和贝叶斯.

这本书是贝叶斯学派.

最大似然估计,是频率学派.

最大后验估计.

理论讲的比较少.

SVM讲的比较少.(本质上是优化模型,是概率)

另外一本书:Foundations of Machine Learning(从理论开始讲起)

Deep learning (Bengio)

online resourcce:

Andre Ng

高维数据()

降维.lasso.

一般来说,要feature要小于sample size.

可以降维.

问题:

数据越来越高维, 怎么让数据量足够handle?

gradient descent(梯度下降)

step依靠经验去挑选.

training and test data的误差都要比较小才比较好.

Hoeffding’s inequality

最为关键的问题,overfitting.

如何克服overfiting?

variance + bias

tradeoff

克服overfiting的方法?

drop off.

Avatar
Xiaotao Shen
Postdoctoral Research Fellow

Metabolomics, Multi-omics, Bioinformatics, Systems Biology.

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