(prob_matrix, threshold=0.5)
return ret
Load tag from file

    Args:
        prob_matrix: probability matrix have the shape of (data_num, class_num), 
            type of float. Generated from sigmoid activation
        threshold: when larger than threshold, consider it as true or else false
    Returns:
        ret: for each case, set all positive class to 1, shape of(data_num, class_num)
Load tag from file
Load tag from file
def pred_from_prob_sigmoid(prob_matrix, threshold=0.5):
    """
    Load tag from file

    Args:
        prob_matrix: probability matrix have the shape of (data_num, class_num), 
            type of float. Generated from sigmoid activation
        threshold: when larger than threshold, consider it as true or else false
    Returns:
        ret: for each case, set all positive class to 1, shape of(data_num, class_num)
    """
    np_matrix = np.array(prob_matrix)
    ret = (np_matrix > threshold)*1
    return ret
def pred_from_prob_sigmoid ( prob_matrix , threshold = 0.5 ) : np_matrix = np . array ( prob_matrix ) ret = ( np_matrix > threshold ) * 1 return ret