Add to ORKGAnother popular technique for classification (or at least, which used to be popular) is the (linear) discriminant analysis, introduced by Ronald Fisher in 1936. Consider the same dataset as in our previous post clr1 - c(rgb(1,0,0,1),rgb(0,0,1,1)) x - c(.4,.55,.65,.9,.1,.35,.5,.15,.2,.85) y - c(.85,.95,.8,.87,.5,.55,.5,.2,.1,.3) z - c(1,1,1,1,1,0,0,1,0,0) df - data.frame(x,y,z) plot(x,y,pch=19,cex=2,col=clr1[z+1]) The main interest of that technique is not the output, but more the fact ..
The applications that are related to classification problem are wide-ranging. In fact, differentiati...
Eighth post of our series on classification from scratch. The latest one was on the SVM, and today, ...
<p>Discriminant variables and their coefficients are shown, with the top 5 discriminant variables in...
peer-reviewedFisher's linear discriminant analysis is one of the most commonly used and studied clas...
This study provides a comprehensive review of the literature pertaining to the problem of classifica...
Discriminant analysis is a multivariate statistical technique used primarily for obtaining a linear ...
The technique of discriminant function analysis was originated by R.A. Fisher and first applied by B...
In our data-science class, after discussing limitations of the logistic regression, e.g. the fact th...
We will start, in our Data Science course, to discuss classification techniques (in the context of ...
Linear discriminant analysis (LDA) is a part of classification methods that has been widely used in ...
Abstract: Linear discriminant analysis is typically carried out using Fisher’s method. This method r...
I have researched in the field of discriminant analysis for over 40 years and for nearly as long in ...
The use of miltivariate statistics in the social and behavioral'sciences is becoming more and m...
The performance of four discriminant analysis procedures for the classification of observations from...
Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on ...
The applications that are related to classification problem are wide-ranging. In fact, differentiati...
Eighth post of our series on classification from scratch. The latest one was on the SVM, and today, ...
<p>Discriminant variables and their coefficients are shown, with the top 5 discriminant variables in...
peer-reviewedFisher's linear discriminant analysis is one of the most commonly used and studied clas...
This study provides a comprehensive review of the literature pertaining to the problem of classifica...
Discriminant analysis is a multivariate statistical technique used primarily for obtaining a linear ...
The technique of discriminant function analysis was originated by R.A. Fisher and first applied by B...
In our data-science class, after discussing limitations of the logistic regression, e.g. the fact th...
We will start, in our Data Science course, to discuss classification techniques (in the context of ...
Linear discriminant analysis (LDA) is a part of classification methods that has been widely used in ...
Abstract: Linear discriminant analysis is typically carried out using Fisher’s method. This method r...
I have researched in the field of discriminant analysis for over 40 years and for nearly as long in ...
The use of miltivariate statistics in the social and behavioral'sciences is becoming more and m...
The performance of four discriminant analysis procedures for the classification of observations from...
Linear discriminant analysis is typically carried out using Fisher’s method. This method relies on ...
The applications that are related to classification problem are wide-ranging. In fact, differentiati...
Eighth post of our series on classification from scratch. The latest one was on the SVM, and today, ...
<p>Discriminant variables and their coefficients are shown, with the top 5 discriminant variables in...