模型选择# 与 sklearn.model_selection module. 平衡模型复杂性和交叉验证分数 Balance model complexity and cross-validated score 比较随机搜索和网格搜索用于超参数估计 Comparing randomized search and grid search for hyperparameter estimation 网格搜索和连续减半的比较 Comparison between grid search and successive halving 混淆矩阵 Confusion matrix 具有交叉验证的网格搜索自定义改装策略 Custom refit strategy of a grid search with cross-validation 基于cross_val_score和GridSearchCV的多度量评估演示 Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV 模型正规化对训练和测试误差的影响 Effect of model regularization on training and test error 嵌套与非嵌套交叉验证 Nested versus non-nested cross-validation 绘制交叉验证预测 Plotting Cross-Validated Predictions 绘制学习曲线并检查模型的可扩展性 Plotting Learning Curves and Checking Models' Scalability 事后调整决策函数的截止点 Post-hoc tuning the cut-off point of decision function pr曲线 Precision-Recall 具有交叉验证的接收器工作特性(ROC) Receiver Operating Characteristic (ROC) with cross validation 用于文本特征提取和评估的样本管道 Sample pipeline for text feature extraction and evaluation 使用网格搜索进行模型统计比较 Statistical comparison of models using grid search 连续减半迭代 Successive Halving Iterations 用排列测试分类分数的重要性 Test with permutations the significance of a classification score 不足与过度贴合 Underfitting vs. Overfitting 在scikit-learn中可视化交叉验证行为 Visualizing cross-validation behavior in scikit-learn