linear discriminant analysis python

From: http://blog.csdn.net/warmyellow/article/details/5454943 I. lda algorithm Overview: Linear Discriminant Analysis (LDA), also known as Fisher linear discriminant, is a classic algorithm for pattern recognition, it introduced Pattern Recognition and AI by belhumeur in 199

') plt.ylabel (' Ratio_sugar ') plt.title (' LDA ') plt.show () W=calulate_w () plot (W)The results are as follows: The corresponding W value is:[ -6.62487509e-04, -9.36728168e-01]Because of the relationship between data distribution, LDA's effect is not obvious. So I changed the number of samples of several label=0, rerun the program to get the result as follows:The result is obvious, the corresponding W value is:[-0.60311161,-0.67601433]Transferred from: http://cache.baiducontent.com/c?m= 9d7

Introduction to LDA algorithmA LDA Algorithm Overview:Linear discriminant Analysis (Linear discriminant, LDA), also called Fisher Linear discriminant (Fisher Linear

1. What is lda? Linear Discriminant Analysis (LDA. Fisher Linear Discriminant (linear) is a classic algorithm for pattern recognition. In 1996, belhumeur introduced Pattern Recognition and AI. The basic idea is to project a high-d

Introduction to LDA algorithmA. LDA Algorithm Overview:Linear discriminant Analysis (Linear discriminant, LDA), also called Fisher Linear discriminant (Fisher Linear

Linear discriminant Analysis (Linear discriminant Analyst) (i)1. QuestionsBefore we discussed the PCA, ICA or the sample data to say, can be no category tag Y. Recall that when we do the regression, if there are too many features, then there will be irrelevant features intro

Linear discriminant Analysis (Linear discriminant Analyst) (ii)4. ExampleThe spherical sample points on the 3-dimensional space are projected onto two dimensions, and W1 can achieve better separation than W2.Comparison of the dimensionality reduction between PCA and LDA:The

Mathematics in Machine learning (4)-Linear discriminant analysis (LDA), principal component analysis (PCA)Copyright Notice:This article is published by Leftnoteasy in Http://leftnoteasy.cnblogs.com, this article can be reproduced or part of the use, but please indicate the source, if there is a problem, please contact

classification degree. Ronald Fisher presented a linear discriminant (Problems Linear) method in 1936 (the "Use of multiple measurements in taxonomic discriminant"), which is sometimes used to solve classification questions Problem. The initial linear

of the solution of a matrix eigenvalue problem, but understand how to deduce, in order to understand the meaning of the deeper. This content requires the reader to have some basic linear algebra basis, such as eigenvalue, eigenvector concept, space projection, point multiplication and other basic knowledge. In addition to the other formulas, I try to speak more simple and clear.Lda:The full name of LDA is linear