In supervised learning, we are interested in developing a model to predict a class label given an example of input variables. This predictive modeling task is called classification.

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

Supervised and unsupervised learning describe two ways in which machines - algorithms - can be set loose on a data set and expected to learn something useful from it.

There are two main types of supervised learning: classification and regression. Classification. Classification is when the output variable is categorical, with two or more classes that the model ...

The performance of regression methods for selecting the best individuals was compared with that of three supervised classification algorithms ... Machine learning algorithms, whether regression ...