python SVM调包线性分类西瓜

import xlrd
import numpy as np
from sklearn.model_selection import KFold
from sklearn.model_selection import cross_val_score
from sklearn.svm import SVC

data = xlrd.open_workbook('gua.xlsx')
sheet = data.sheet_by_index(0)
Density = sheet.col_values(6)
Sugar = sheet.col_values(7)
Res = sheet.col_values(8)

# 读取原始数据
X = np.array([Density, Sugar])
# y的尺寸为(17,)
y = np.array(Res)
X = X.reshape(17, 2)
num_folds = 10
seed = 7
kfold = KFold(n_splits=num_folds, random_state=seed)
model = SVC()
result = cross_val_score(model, X, y, cv=kfold)
print(result.mean())