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 ...

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

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.

The earlier AdaBoost.R algorithm was a suggestion in the original 1995 AdaBoost binary classification research paper by Y. Freund and R. Schapire, ... The AdaBoost.R2 regression algorithm has not ...

To evaluate the diagnostic accuracy of an algorithm, it can be compared to the best existing classification for the used dataset, for which the value 100 percent is assigned.