machine learning (6)---how to choose features, polynomial regression

①假设函数(hypothesis function) 在给定一些样本数据(training set)后,采用某种学习算法(learning algorithm)对样本数据进行训练,得到了一个模型或者说是假设函数. 当需要预测新数据的结果时,将新数据作为假设函数的输入,假设函数计算后得到结果,这个结果就作为预测值. 假设函数的表示形式一般如下:θ 称为模型的参数(或者是:权重weights),x就是输入变量(input variables or feature variables) 可以看出,假设

Awesome Machine Learning  A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php. If you want to contribute to this list (please do), send me a pull request or contact me @josephmisiti Als

(1) How to comput the Cost function in Univirate/Multivariate Linear Regression; (2) How to comput the Batch Gradient Descent function in Univirate/Multivariate Linear Regression; (3) How to scale features by mean value and standard deviation; (4) Ho

参考: Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation 前所未有!10篇<Cell>文章及封面聚焦人类伟大成就:癌症基因组图谱TCGA!改写教科书式突破! “癌症大地图”(Pan-Cancer Atlas) 肿瘤界“巅峰之作”:美国推出“泛癌症图谱”服务全人类 文章代码: PanCanStem 文档 相关培训: 待续~ 原文地址:https://www.cnblo

Machine Learning for Developers Most developers these days have heard of machine learning, but when trying to find an 'easy' way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learnin

第二周 第一部分 Multivariate Linear Regression Multiple Features Note: [7:25 - θT is a 1 by (n+1) matrix and not an (n+1) by 1 matrix] Linear regression with multiple variables is also known as "multivariate linear regression". We now introduce notatio

COMMON PITFALLS IN MACHINE LEARNING JANUARY 6, 2015 DN 3 COMMENTS Over the past few years I have worked on numerous different machine learning problems. Along the way I have fallen foul of many sometimes subtle and sometimes not so subtle pitfalls wh

发现自己不写总结真是件很恶劣的事情,好多学的东西没有自己总结都忘记了.所以决定从今天开始,学东西的时候一定跟上总结. 我写的东西大多数是自己通俗的总结,不太喜欢写严格的定义或者证明,写了也记不住,欢迎指正. 1. High Bias vs. High Variance High Bias:通常是因为模型过于简单,使得不能成功拟合数据.比如说一些有二次曲线特性的数据,如果用一次直线去拟合就会出现这个问题,所以它对应了Underfitting问题.另外,从泛化角度来说,这样的模型泛化程度更高. Hi

Introduction Optimization is always the ultimate goal whether you are dealing with a real life problem or building a software product. I, as a computer science student, always fiddled with optimizing my code to the extent that I could brag about its