插入数据
在X的第一列插入1
X = np
.insert(
X,
0, values = np
.ones(
X.shape[
0]), axis =
1)
随机选取一些数据
在X中随机选取100个样本
sample_id = np
.random.choice(np
.arange(
X.shape[
0]),
100)
优化训练
用到的时候查一下文档
import scipy.optimize
as opt
res = opt.minimize(fun = cost_function, x0 = theta, args = (X, y, learning_rate),
method = 'TNC', jac = cost_function_gradient, options = )
final_theta = res.x
轴向最大值的索引
y_pred =
np.argmax(prob_matrix, axis = 1)
加载matlab数据
from scipy.io
import loadmat
data = loadmat('filename.mat')
data
