Logistic vs Softmax

logistic函数也是神经网络最为常用的激活函数，即sigmoid函数, 应用于分类和回归
logistic具体针对的是二分类问题，

 softmax函数经常用在神经网络的最后一层，作为输出层，解决的是多分类问题，因此从这个角度也可以理解logistic函数是softmax函数的一个特例。
softmax建模使用的分布是多项式分布，而logistic则基于伯努利分布

 softmax回归进行的多分类，类与类之间是互斥的，即一个输入只能被归为一类；
多个logistic回归进行多分类，输出的类别并不是互斥的，即"苹果"这个词语既属于"水果"类也属于"食物"类别。

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