Multiclass classification
The classification you have seen and experienced so far is a two-class classification where the target variable can be of two classes. In multiclass classification, you classify in more than two classes, for example continuing on our hypothetical tumor problem, for a given tumor size and age of a patient, you might predict one of these three classes as the possibility of a patient being affected with cancer: High, Medium, and Low. In theory, a target variable can have any number of classes.
Evaluation metrics – multiclass classification
ML Studio lets you evaluate your model with an accuracy that is calculated as a ratio of the number of correct predictions versus the incorrect ones. Consider the following table:
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