Machine Learning Series No.6 -- EM algorithm EM算法 1.直观理解 通俗理解:https://blog.csdn.net/v_JULY_v/article/details/81708386 通俗的理解看出就是EM算法由于不知道隐变量的分布,先给出参数的随机初始值,然后根据参数,去得到隐变量的分布,然后根据隐变量和观测变量的共同分布基于最大似然去重新估计参数...
当协方差矩阵各向同性时,w与类中心向量平行(同LDA)。 注:PCA也可通过特征值分解进行降维,把数据投影到特征值(方差)最大的方向,但降维后数据不一定可分。
二、EM算法简介 在上述存在隐变量的问题中,不能直接通过极大似然估计求出模型中的参数,EM算法是一种解决存在隐含变量优化问题的有效方法。EM算法是期望极大(Expectation Maximization)算法的简称,EM算法是一种迭代型的算法,在每一次的迭代过程中,主要分为两步:即求期望(Expectation)步骤和最大化(Maximization)步骤。
The example of EM algorithm to solve the problem in page 137 of Machine Learning book(Chinese Edition) written by Tom M. Mitchell. ##EM算法一般表述: 当有部分数据缺失或者无法观察到时,EM算法提供了一个高效的迭代程序用来计算这些数据的最大似然估计。在每一步迭代分为两个步骤: 期望(Expectation)步骤...
Machine Learning—Mixtures of Gaussians and the EM algorithm 印象笔记同步分享:Machine Learning—Mixtures of Gaussians and the EM algorithm
QInzhengk/Math-Model-and-Machine-Learning (github.com) 一、K近邻算法(KNN)(监督学习算法) 1. 什么是KNN 1.1 KNN的通俗解释 何谓K近邻算法,即K-Nearest Neighbor algorithm,简称KNN算法,单从名字来猜想,可以简单粗暴的认为是:K个最近的邻居,当K=1时,算法便成了最近邻算法,即寻找最近的那个邻居。
Running the example fits the Gaussian mixture model on the prepared dataset using the EM algorithm. Once fit, the model is used to predict the latent variable values for the examples in the training dataset. Note: Your results may vary given the stochastic nature of the algorithm or evaluation...
一、概念 二、应用场景距离 计算案例 案例优化 图解步骤 一、概念 顾名思义: 最大期望算法(Expectation Maximization Algorithm,又译期望最大化算法),是一种迭代算法,用于含有隐变量(latent variable)的概率... 机器学习_EM算法 Jesen不等式 若f是凸函数(如f(x)=x2f(x)=x^2f(x)=x2),则f(Ex)≤E(f(...
Aligning text and phonemes for speech technology applications using an EM-like algorithm - Damper, Marchand, et al. - 2005 () Citation Context ...he machine-learning based approaches is to establish the relations between the two sequences, i.e., between the letters and the phonemes in the...
example, "powerful," "strong" and "Paris" are equally distant. In this paper, we propose an unsupervised algorithm that learns vector representations of sentences and text documents. This algorithm represents each document by a dense vector which is trained to predict words in the document. Its...