Machine learning algorithms for predicting or categorizing data include classification and regression techniques. Regression algorithms are used to forecast a continuous numerical value, such as the ...

Which kind of algorithm works best (supervised, unsupervised, classification, regression, etc.) depends on the kind of problem you’re solving, the computing resources available, and the nature ...

Application: support vector machines regression algorithms has found several applications in the oil and gas industry, classification of images and text and hypertext categorization. In the oilfields, ...

Logistic regression. Classification algorithms can find solutions to supervised learning problems that ask for a choice (or determination of probability) between two or more classes.

Abstract: This article proposes an algorithm for solving multivariate regression and classification problems using piecewise linear predictors over a polyhedral partition of the feature space. The ...

The behaviour of regression and classification algorithms varied markedly when selection was done at different thresholds, that is, ...

Using different classification algorithms, Logistic regression, Neural Network, SVM, Random Forest) on MNIST data for predicting digits. Problem Statement-: The problem is about recognizing the 28 X ...