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Introduction of EM algorithmIn one of the EM algorithm-the problem is introduced in the issue of the coin, the object function of the model, mentioned that the maximum likelihood estimation of the implicit variable to be solved with the EM algorithm,

Logistic regression is a classification algorithm which can deal with two-tuple classification and multivariate classification. Although its name contains "regression" two words, but not a regression algorithm. So why is there a misleading word for "

Supervised learningFor a house price forecasting system, the area and price of the room are given, and the axes are plotted by area and price, and each point is drawn.Defining symbols:\ (x_{(i)}\) represents an input feature \ (x\).\ (y_{(i)}\)

Introduction of EM algorithm In one of the EM algorithm-the problem is introduced in the issue of the coin, the object function of the model, mentioned that the maximum likelihood estimation of the implicit variable to be solved with the EM

The model of text subject LDA (i) LDA FoundationThe model of the text subject LDA (ii) The Gibbs sampling algorithm for LDA solutionLDA of the text subject model (iii) The variational inference EM algorithm for LDA solutionThis article is the third

The 9th Chapter EM algorithm and its generalization EM algorithm is an iterative algorithm, which is used for maximum likelihood estimation of probabilistic model parameters with implicit variables (hidden variable), or maximal posteriori

This article mainly introduces 97 kinds of curve equations commonly used in proe, the coordinate system used, and the legends for generating curves.  The curve types on each page are as follows:Page 1: disc spring, spiral, helical curve,

In English phonetics, the hardest thing for Chinese to learn is today's pair, theta and D. It looks strange, what a good side to do, speak to the tongue out, not a bit beautiful greasy. Indeed, in general, this tone has to be used to bite the tip of

I. Limitations of logistic regressionIn the logistic regression section, using the multi-classification of logistic regression, we realized the numbers on the image that recognize 20*20.But the use of a first-order model, and did not use the

Logistic regressionTypically a two-tuple classifier (also available for multivariate classification), such as the following classification problems Email:spam/not spam Tumor:malignant/benign Suppose (hypothesis): $ $h _\theta (x) =