我尝试将我的sklearn代码迁移到基本二进制分类示例上的keras。我对返回与sklearn不同的keras predict()方法有疑问。
print("X_test:")
print(X_test)
y_pred = model.predict(X_test)
print("y_pred:")
print(y_pred)
XGBClassifier（base_score=0.5，colsample_bylevel=1，colsample_bytree=1，gamma=0，learning_rate=0.1，max_delta_step=0，max_depth=3，min_child_weight=1，missing=None，n_estimators=100，nthread=-1，objective='二元：逻辑'，reg_alpha=0，reg_lambda=1，scale_pos_weight=1，seed=0，silent=True，subsample=1）
--- 预测 Sklearn ---
X_test: [[ 1. 90. 62. ..., 27.2 0.58 24. ] [ 7. 181. 84. ..., 35.9 0.586 51. ] [ 13.
152. 90. ..., 26.8 0.731 43. ] ] ..., [ 4. 118. 70. ..., 44.5 0.904 26. ] [ 7. 152. 88. ..., 50. 0.337 36. ] [ 7. 168. 88. ..., …