utils.py 文件源码

def self_eval(pred,train_data):
    '''
    :pred 
    :train_data ?? labels
    '''
    try:
        labels=train_data.get_label()
    except:
        labels=train_data
    epsilon = 1e-15
    pred = np.maximum(epsilon,  pred)
    pred = np.minimum(1-epsilon,pred)
    ll = sum(labels*np.log(pred) + (1 - labels)*np.log(1 - pred))
    ll = ll * (-1.0)/len(labels)
    return 'log loss', ll, False