小编jat*_*tin的帖子

关于stackoverflow的类似问题的答案建议更改实例SVR（）中的参数值，但我不知道如何处理它们。

这是我正在使用的代码：

import json
import numpy as np
from sklearn.svm import SVR

f = open('training_data.txt', 'r')
data = json.loads(f.read())
f.close()

f = open('predict_py.txt', 'r')
data1 = json.loads(f.read())
f.close()

features = []
response = []
predict = []

for row in data:
    a = [
        row['star_power'],
        row['view_count'],
        row['like_count'],
        row['dislike_count'],
        row['sentiment_score'],
        row['holidays'],
        row['clashes'],
    ]
    features.append(a)
    response.append(row['collection'])

for row in data1:
    a = [
        row['star_power'],
        row['view_count'],
        row['like_count'],
        row['dislike_count'],
        row['sentiment_score'],
        row['holidays'],
        row['clashes'],
    ]
    predict.append(a)

X = np.array(features).astype(float)
Y = np.array(response).astype(float)
predict = np.array(predict).astype(float)

svm …