Types of Multi Classification

This blog introduces different types of multi classification systems.

Multiclass Classification

Multiclass classifiers can distinguish between more than two classes other than binary classifiers. Stochastic gradient descent (SGD) classifiers, Random Forest classifiers, and naive Bayes classifiers etc. are capable of handling multiple classes natively. On the other hand, Logistic Regression or Support Vector Machine classifiers are strictly binary classifiers.

Multilabel Classification

In some cases, we may want the classifier to output multiple classes for each instance. A classification system that outputs multiple binary tags is called a multilabel classification system.

Multioutput Classification

For multioutput classification, it is a generalization of multilabel classification where each label can be multiclass (i.e., it can have more than two possible values). Multioutput systems are not limited to classification tasks, we could even have a system that outputs multiple labels per instance, including both class labels and value labels.

What happened couldn’t have happened any other way…