Lecture2 Linear methods for regression, Optimization

【Lecture2 Linear methods for regression, Optimization】的更多相关文章

ESL翻译：Linear Methods for Regression

chapter 3: Linear Methods for Regression 第3章:回归的线性方法 3.1 Introduction A linear regression model assumes that the regression function \(E(Y\mid X)\) is linear in the inputs \(X_1, \ldots , X_p\). Linear models were largely developed in the precomputer…

Linear and Logistic Regression in TensorFlow

Linear and Logistic Regression in TensorFlow Graphs and sessions TF Ops: constants, variables, functions TensorBoard Lazy loading Linear Regression: Predict life expectancy from birth rate Let's start with a simple linear regression example. I hope y…

[Scikit-learn] 1.1 Generalized Linear Models - Lasso Regression

Ref: http://blog.csdn.net/daunxx/article/details/51596877 Ref: https://www.youtube.com/watch?v=ipb2MhSRGdw Ref: nullege.com/codes Lasso Regression |-- Coordinate descent |-- Least Angle Regression |-- ElasticNet |-- Compressive sensing Lasso回归模型是一个用…

[Scikit-learn] 1.1 Generalized Linear Models - Logistic regression & Softmax

二分类:Logistic regression 多分类:Softmax分类函数对于损失函数,我们求其最小值, 对于似然函数,我们求其最大值. Logistic是loss function,即: 在逻辑回归中,选择了 “对数似然损失函数”,L(Y,P(Y|X)) = -logP(Y|X). 对似然函数求最大值,其实就是对对数似然损失函数求最小值. Logistic regression, despite its name, is a linear model for classification…

PRML读书笔记——3 Linear Models for Regression

Linear Basis Function Models 线性模型的一个关键属性是它是参数的一个线性函数,形式如下: w是参数,x可以是原始的数据,也可以是关于原始数据的一个函数值,这个函数就叫basis function,记作φ(x),于是线性模型可以表示成: w0看着难受,定义一个函数φ0(x) = 1, 模型的形式再一次简化成: 以上就是线性模型的一般形式.basis function有很多选择,例如Gaussian.sigmoid.tanh (tanh(x) = 2 * sigmoid(…

PRML读书会第三章 Linear Models for Regression(线性基函数模型、正则化方法、贝叶斯线性回归等)

主讲人 planktonli planktonli(1027753147) 18:58:12 大家好,我负责给大家讲讲 PRML的第3讲 linear regression的内容,请大家多多指教,群主让我们每个主讲人介绍下自己,赫赫,我也说两句,我是 applied mathematics + computer science的,有问题大家可以直接指出,互相学习.大家有兴趣的话可以看看我的博客: http://t.qq.com/keepuphero/mine,当然我给大家推荐一个好朋友的,他对…

PRML-Chapter3 Linear Models for Regression

Example: Polynomial Curve Fitting The goal of regression is to predict the value of one or more continuous target variables t given the value of a D-dimensional vector x of input variables. 什么是线性回归?线性回归的目标就是要根据特征空间是D维的输入x,预测一个或多个连续的目标值变量,大多数情况下我们研究的目…