# Kohonen in java

The following java project contains the java source code and java examples used for kohonen. This code is a homework for my University. It uses AI concepts to simulate a Kohonen Neural Network. Enjoy it and don't forgert to vote.

The following Matlab project contains the source code and Matlab examples used for kernel smoothing regression.
Non-parametric regression is widely used in many scientific and engineering areas, such as image processing and pattern recognition.

The following Matlab project contains the source code and Matlab examples used for multivariate gaussian mixture model optimization by cross entropy.
Fit a multivariate gaussian mixture by a cross-entropy method.

The following Matlab project contains the source code and Matlab examples used for caim discretization algorithm.
The task of extracting knowledge from databases is quite often performed by machine learning algorithms.

The following Matlab project contains the source code and Matlab examples used for kernel density estimator.
% Reliable and extremely fast kernel density estimator for one-dimensional data;
% Gaussian kernel is assumed and the bandwidth is chosen automatically;
% Unlike many other implementations, this one is immune to problems
% caused by multimodal densities with widely separated modes (see example).

The following Matlab project contains the source code and Matlab examples used for clustering through optimal bayesian classification.
A new soft clustering algorithm is presented (Clustering through Optimal Bayesian Classification).

The following Matlab project contains the source code and Matlab examples used for similarity classifier.
This classifier is based on the idea that first we create ideal vectors from each class.

The following Matlab project contains the source code and Matlab examples used for pls regression or discriminant analysis, with leave one out cross validation and prediction..
Leave-one-out cross-validation for PLS regression or discriminant analysis
pls_cv = plscv(x,y,vl,'da')
input:
x (samples x descriptors) for cross-validation
y (samples x variables) for regression or
(samples x classes) for discriminant analysis.

The following Matlab project contains the source code and Matlab examples used for sparse representations classifier.
#The kernel sparse representations classifier implemented here is
# based on the paper
1)Robust Face Recgnition via Sparse Representation John Wright, Student Member, Allen Y.

The following Matlab project contains the source code and Matlab examples used for naive bayes classifier.
I use Matlab 2008a which does not support Naive Bayes Classifier.

The following Matlab project contains the source code and Matlab examples used for performance measures for classification.
Classification models in machine learning are evaluated for their performance by common performance measures.

The following Matlab project contains the source code and Matlab examples used for mweka running machine learning tool weka from matlab.
This GUI runs the weka classifiers and displays the results in MATLAB.

The following Matlab project contains the source code and Matlab examples used for similarity classifier with owa operators.
Similarity classifier with OWA operators toolbox presents vector based classification method which uses similarity measures and OWA operators to make a distiction to which class samples belong.

The following Matlab project contains the source code and Matlab examples used for gaussian mixture model.
Gaussian Mixture model is used in many fields to model a training set of data owing to certain similarities among them.

The following Matlab project contains the source code and Matlab examples used for bivariate kernel regression with restrictions.
bivkernrest returns the marginal kernel densities of the two input data series, the bivariate kernel density, the conditional kernel densities, and the conditional expectations.

The following Matlab project contains the source code and Matlab examples used for kernel density estimation.
** Please also check ssvkernel.

The following Matlab project contains the source code and Matlab examples used for this is the code of a novel metric learning algorithm, which is fast and accurate. .
This is the code of our new metric learning algorithm which is presented in "Jiangyuan Mei, Meizhu Liu, Hamid Reza Karimi, and Huijun Gao, "LogDet Divergence based Metric Learning with Triplet Constraints and Its Applications", IEEE Transactions on image processing, under review.

The following Matlab project contains the source code and Matlab examples used for low rank multivariate autoregressive model for dimensionality reduction.
Despite the fact that they do not consider the temporal nature of data, classic dimensionality reduction techniques, such as PCA, are widely applied to time series data.

The following Matlab project contains the source code and Matlab examples used for kernel density estimation for circular functions.
See also http://dylan-muir.

The following Matlab project contains the source code and Matlab examples used for true positives, false positives, true negatives, false negatives from 2 matrices.
- This simple function takes in 2 matrices of equal size populated with 1's and 0's and returns the number of True Positives, False Positives, True Negatives, False Negatives in order for precision and recall calculation
- 1st matrix is the true matrix
- 2nd matrix is the one populated from an algorithm used
- Returns error metrics based on a binary classification.

The following Matlab project contains the source code and Matlab examples used for bayesian linear classifier.
This function uses Bayesian inference to find the optimal linear separator in a binary classification problem.

The following Matlab project contains the source code and Matlab examples used for gaussian mixture model.
A Gaussian mixture model means that each data point is drawn (randomly) from one of C classes of data, with probability p_i of being drawn from class i, and each class is distributed as a Gaussian with mean standard deviation mu_i and sigma_i.

The following Matlab project contains the source code and Matlab examples used for support vector regression.
Support Vector Regression is a powerful function approximation technique based on statistical learning theory.

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.

The following Matlab project contains the source code and Matlab examples used for fast null linear discriminant analysis.
Null linear discriminant analysis (LDA) method is a popular dimensionality reduction method for solving small sample size problem.

The following Matlab project contains the source code and Matlab examples used for discriminant analysis via support vectors.
In this paper, we show how support vector machine (SVM) can be
employed as a powerful tool for $k$-nearest neighbor (kNN)
classifier.

The following Matlab project contains the source code and Matlab examples used for efficient k nearest neighbor search using jit.
This is a small but efficient tool to perform K-nearest neighbor search, which has wide Science and Engineering applications, such as pattern recognition, data mining and signal processing.

The following Matlab project contains the source code and Matlab examples used for k nearest neighbor search.
This is just a brute force implementation of k nearest neighbor search without using any fancy data structure, such as kd-tree.

The following Matlab project contains the source code and Matlab examples used for simple perceptron.
Perceptron is an algorithm for supervised classification of an input into one of several possible non-binary outputs. This mfile is a simple type of perceptron to who like to learn about the perceptron type of artificial neural networks

The following Matlab project contains the source code and Matlab examples used for a probabilistic model of classifier competence.
In pattern recognition a common problem is to calculate competence of a classifier for a given object.