This chapter treats multiclass classification.
In this section, we introduce the basic concepts in multiclass classification and important multiclass losses: MC 0-1-loss, MC brier score, MC logarithmic loss.
In this section, we introduce softmax regression as a generalization of logistic regression.
In this section, we discuss two ways how to reduce a multiclass problem to multiple binary classification problems: one-vs-one and one-vs-rest.
In this section, we introduce codebooks as a general concept for multiclass to binary reduction.