Implementation of Fast Orthogonal Search (FOS) Algorithm in MATLAB

Randomized Greedy Polynomial Chaos Expansions

Machine Learning Exercises from Online Course (Coursera)

Here, we implement regularized linear regression to predict the amount of water flowing out of a dam using the change of water level in a reservoir. In the next half, we go through some diagnostics of debugging learning algorithms and examine the effects of bias v.s. variance.

Regularized least-squares algorithm over the empirical risk minimization

Classification of Breast Lesion contours to Benign and Malignant Categories.

Attempt to use Machine Learning to predict natural gas consumption for domestic needs

it's a standard approach in regression analysis to approximate the solution of overdetermined systems (sets of equations in which there are more equations than unknowns)

Polynomial Regression

CourseRoom Bridge Used By CourseRoom Calculator To Run Evolutive Polinization Optimization Algorithm To Resolve Lineal And Polynomial Regression To Predict Scores

Implementation of transfer learning approaches for predictive modeling of anticancer drug sensitivity.

Fitting module. Used for establishing functions/linkages between material descriptors and process or property parameters.

Starting from a dataset, which concerns two years gas consumption trend in Italy in function of two parameters (day of the year, day of the week), we want to identify the model which represents our data in the better way. Afterwards, we created a function that predicts the gas consumption value, using the best identified model, once you insert a…

Curve fitting - 1st, 2nd order polynomial ; Linear and spline interpolations -- Sample problems

With OCTAVE - For the exercises details, kindly read ex1.pdf in the repo.

Exercises and assignments made during a Computational Intelligence class at Federal University Of Ceará.

Machine Learning using Matlab

Algorithms developed in the Computational Intelligence class

Exploring methods to solve a systems of linear equations and least squares problems

This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.