SVMs are supervised learning models with associated learning algorithms that analyze data for classification and regression analysis. Like many classification and prediction methods, SVMs classify ...

Machine learning algorithms are the engines ... Which kind of algorithm works best (supervised, unsupervised, classification, regression, etc.) depends on the kind of problem you’re solving ...

We have previously discussed several supervised learning algorithms, including logistic regression and random ... we will apply them to classification, because they tend to perform better at ...

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

Supervised and unsupervised learning describe two ways in which machines - algorithms - can be set ... to match into groups according to their classification and color (a common problem in machine ...