Author Archives: Nidhika

Feature Selection Techniques using Evolutionary Algorithms

This article describes application of Evolutionary Algorithms to the task of Feature Selection. In particular the algorithms studies in this article are Particle Swarm Algorithm (PSO) and Genetic Algorithm (GA). The results are based on particular parameters used in experimentation. Here several parameters are analyzed for this problem on two datasets: Leukemia dataset (LIBSVM Data:Continue reading “Feature Selection Techniques using Evolutionary Algorithms”

Function Optimization using Genetic Algorithm and Particle Swarm Optimization-Results and Comparison

In this article some experiments and their results are discussed for minimization of Rastrigin function, a famous mathematical function used in Optimization Techniques evaluation. The experiments are performed on certain setup, parameters and system. This has been performed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The fitness function is the given function toContinue reading “Function Optimization using Genetic Algorithm and Particle Swarm Optimization-Results and Comparison”

2-class Image Recognition Task using Backpropagation, Regularized Neural Networks, Logistic Regression and Naive Bayes-Code, Results and Analysis for given Implementation

This article is for education and learning purpose. The aim is to understand how to start experimentation in the area of Neural Networks, how to compare results, what all features to consider while doign experiments. It is a handy tool for those doing self learning in the area of Machine Learning. And a good startContinue reading “2-class Image Recognition Task using Backpropagation, Regularized Neural Networks, Logistic Regression and Naive Bayes-Code, Results and Analysis for given Implementation”

Some Graphical Comparison and Results (with fitted polynomials) of Naive Bayes, Logistic Regression and Linear Regression

This article provides results, graphical plots and analysis of Linear, Logistic Regression, Naive Bayes for three kinds of datasets, namely, (i) Linearly Seperable, (ii) Non-Linearly Seperable and (iii) Banana Data. This article plays a good role for new mentors, academicians and students to understand the process of experimentations and analysis, result presentation in a MachineContinue reading “Some Graphical Comparison and Results (with fitted polynomials) of Naive Bayes, Logistic Regression and Linear Regression”

Logistic Regression Matlab Code-Iterative

% this is for two class problem for more than two class code changes % % this is for two class problem for more than two class code changes% % ————-Parameters————-% numIteration =1000; The Number of maximum iterations% % errorBound = 0.0001; This is the permissible error.% The experiments have been done keep in viewContinue reading “Logistic Regression Matlab Code-Iterative”

Glimpse of Regression Codes in Matlab

Preprocessing: I have created three .mat files from the given input in form of a text file. I first imported it in xls and then copied it to .mat files. NOTE: The derivation for linear and logistic regression is added at the end of the document. Linear Regression Classifier I  have split the datasets intoContinue reading “Glimpse of Regression Codes in Matlab”

Matlab code for Newtons optimization for Logistic Regression

% % this is for two class problem for more than two class code changes% % ————-Parameters————-% numIteration =1000; The Number of maximum iterations% % errorBound = 0.0001; This is the permissible error.% The experiments have been done keep in view both the error condition% reached or maximum iteration reached whichever comes first.% % etaContinue reading “Matlab code for Newtons optimization for Logistic Regression”

Matlab Code for Logistic Regression

% % this is for two class problem for more than two class code changes% % ————-Parameters————-% numIteration =1000; The Number of maximum iterations% % errorBound = 0.0001; This is the permissible error.% The experiments have been done keep in view both the error condition% reached or maximum iteration reached whichever comes first.% % etaContinue reading “Matlab Code for Logistic Regression”

Matlab Linear Regression Sample Code

Three type of datasets have been analyzed for this technique: (1) Linearly separable data(LS) (2) Inseparable data(NLS) (3) Banana data (BD) For a binary classification problem. Split the datasets into 70% training and 30% testing randomly in five folds. This is a old code done as a part of an assignment. Compatibility with newer versionsContinue reading “Matlab Linear Regression Sample Code”