# Statistical classification

# Discriminant analysis concerned with separating distinct sets of observations. in matlab

# Character recognition example (iv) training a simple nn for classification in matlab

# High dimensional data clustering (hddc) in matlab

# Clustering through optimal bayesian classification in matlab

# Similarity classifier in matlab

# Pls regression or discriminant analysis, with leave one out cross validation and prediction. in matlab

# Decision boundary using svms in matlab

# Sparse representations classifier in matlab

# Confusion matrix matching matrix along with precision, sensitivity, specificity and model accuracy in matlab

# Naive bayes classifier in matlab

# Mweka running machine learning tool weka from matlab

# Fast linear binary svm classifier in matlab

# Similarity classifier with owa operators in matlab

# Geometric gaussian kernel bolstered error estimation for linear classification in matlab

# Prepare svm datasets for multi svm in matlab

# Takes in text input, and classifies it into one of five categories. in matlab

# Extended fisher discriminant analysis and point ellipsoid distance in matlab

# Confusion matrix, accuracy, precision, specificity, sensitivity, recall, f score in matlab

# Supervised fuzzy clustering for the identification of fuzzy classifiers in matlab

# True positives, false positives, true negatives, false negatives from 2 matrices in matlab

# Bayesian Classifier Matlab Code

# R peak detection using dwt and classification of arrhythmia using bayesian classifier in matlab

# Bayesian linear classifier in matlab

# Lda Matlab Code

Linear discriminant analysis (LDA) and the related Fisher's linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.

The following matlab project contains the source code and matlab examples used for lda.

# Fast null linear discriminant analysis in matlab

# Linear discriminant analysis code in matlab

# Lda linear discriminant analysis in matlab

# Lda (linear discriminant analysis) in matlab

# Knn Matlab Code

In pattern recognition, the k-Nearest Neighbors algorithm (or k-NN for short) is a non-parametric method used for classification and regression.[1] In both cases, the input consists of the k closest training examples in the feature space.

The following matlab project contains the source code and matlab examples used for knn.