The classifier for word2vec is a binary logistic regression, which applies sigmoid function. given a tuple of words(w,c), where $w$is the target word, $c$is one of the context words: The possibility that $c$ is a context word: $P\left ( +|w,c \right ) = \sigma(c \cdot w)=\frac{1}{1+exp(- , c \cdot w)}$ The possibility that $c$ is not a context word: $P\left ( -|w,c \right ) = 1-P\left ( +|w,c \right )=\sigma(- , c\cdot w)= \frac{1}{1+exp(c \cdot w)}$ But there are several context words: $P\left ( +|w,c_{1:L} \right ) = \prod^L_{i=1}\sigma(c_i \cdot w)=\prod^L_{i=1}\frac{1}{1+exp(- , c_i \cdot w)}$