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尝试使用 statsmodels .predict 预测我的测试值时出现错误。

代码：

X_train, X_test, y_train, y_test = train_test_split(X_new_np, y, test_size=0.2, random_state=42)
logit = sm.Logit(y_train, X_train)
reg = logit.fit_regularized(start_params=None, method='l1_cvxopt_cp', maxiter= 1000, full_output=1, disp=1, callback=None, alpha=.01, trim_mode='auto', auto_trim_tol=0.01, size_trim_tol=0.0001, qc_tol=0.03)
reg.summary()
y_pred_test = logit.predict(X_test)

错误：

ValueError: shapes (1000,61) and (251,61) not aligned: 61 (dim 1) != 251 (dim 0)
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1 回答 1

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您根本没有从正确的对象进行预测。reg是已安装的那个，然后您应该使用reg.predict. 以下代码运行没有错误（我使用了您的 fit_regularized 参数）。

from sklearn.model_selection import train_test_split
import numpy as np
from statsmodels.api import Logit

x = np.random.randn(100,50)
y = np.random.randint(0,2,100).astype(bool)

print(x.shape, y.shape)

X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=.2)

logit = Logit(y_train, X_train)
reg = logit.fit_regularized(start_params=None, method='l1_cvxopt_cp',
        maxiter= 1000, full_output=1, disp=1, callback=None,
        alpha=.01, trim_mode='auto', auto_trim_tol=0.01,
        size_trim_tol=0.0001, qc_tol=0.03)
print(reg.summary())
y_pred_test = reg.predict(X_test)
于 2020-12-20T20:23:08.633 回答