rice_run.py 文件源码

def lr(train_sample, validation_sample, features):
    log_base = np.e
    lr_prob = LinearSVR(C=1, epsilon=0.1).fit(train_sample[features], np.log1p(train_sample['volume'])/np.log(log_base))\
        .predict(validation_sample[features])
    lr_prob = np.power(log_base, lr_prob) - 1
    print_mape(validation_sample['volume'], lr_prob, 'LR')
    return lr_prob