HBLR.py 文件源码

def dataProb(self,new_task_X,new_task_y,weights):
        prod = 1
        for i in range(len(new_task_X)):
            sig = sigmoid(np.dot(weights,np.atleast_2d(new_task_X[i,:]).T ))
            prod = prod*(sig**new_task_y[i]) * (1.0-sig)**(1-new_task_y[i])

        return prod