Two-Category Classifier 1.0

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CreatedCreated : Sep 19, 2007
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Discriminant Functions is one of statistical ...

Discriminant Functions is one of statistical technique used in Pattern Recognition for separating classses.
This is parametric methods, means, it requires that mean and covariance of class is known. In other words, Probability Density of given class should be known to apply this method.
Here, two classes are chosen to obtain optimal decision boundary betwen two classes.
The classes are 2-dimenSional (Bivariate) and 1-dimensional(Univariate).
It is called two-category_classifier by kirit patel. The classifier itself is simplified in three cases:
CASE 1:- In this case feature vectors are statistically independent and covariance matrix is diagonal. samples fall in equal-size spherical clusters.
CASE 2:- In this case feature vectors are statistically dependent but, Covariance matrices are same for both classes. samples fall in equal-size lipsoidal clusters.
CASE 3:- Optimal decision boundary is quadric.
To use this GUI, first unzip the folder. Change current directory to this folder from matlab. Then just type discriminant at MATLAB prompt in Command Window and hit ENTER to open the GUI.
• MATLAB Release: R12

Two-Category Classifier 1.0 scripting tags: covariance, matlab, boundary, clusterscase, two-category classifier, decision, folder. What is new in Two-Category Classifier 1.0 software script? - Unable to find Two-Category Classifier 1.0 news. What is improvements are expecting? Newly-made Two-Category Classifier 1.1 will be downloaded from here. You may download directly. Please write the reviews of the Two-Category Classifier. License limitations are unspecified.