评估与可信
73 种方法属于此方法族。
精选
准确率Accuracy is the proportion of correct predictions among the total number of predictions made by a classification model. It is the most intuitive performance metric and measures how调整R方 (R²_adj)Adjusted R² is a corrected version of the coefficient of determination that accounts for the number of predictors in a regression model. Introduced by Henri Theil in 1961, it addre调整兰德指数The Adjusted Rand Index (ARI), developed by Hubert and Arabie in 1985, is an external clustering evaluation metric that measures the agreement between a predicted clustering and a 赤池信息量准则 (AIC)The Akaike Information Criterion is an information-theoretic measure for model selection that balances goodness of fit against model complexity. Introduced by Hirotugu Akaike in 19平衡准确率Balanced accuracy is the average of recall values computed for each class separately. It corrects for class imbalance by giving equal weight to the performance on each class, regar布里尔分数The Brier score measures the mean squared difference between predicted probabilities and actual binary outcomes. It is a simple, interpretable metric for evaluating the accuracy of
阅读路径
本主题被引用最多的基础方法，按其提出的先后顺序排列——若您初次接触，不妨从这里开始。
全部方法 73
准确率调整R方 (R²_adj)调整兰德指数赤池信息量准则 (AIC)平衡准确率布里尔分数身体形态问卷 (BSQ)Calinski-Harabasz指数量能器校准计算机化自适应测验项目分析混淆矩阵反事实解释戴维斯-布尔丁指数邓恩指数“手肘法”可解释关联规则可解释自编码器异常检测可解释决策树可解释 FP-Growth可解释高斯混合模型可解释高斯过程可解释 HDBSCAN可解释隔离森林可解释K-Means可解释 K-近邻算法可解释 LightGBM可解释朴素贝叶斯可解释单类支持向量机可解释随机森林可解释堆叠集成可解释支持向量机可解释投票集成可解释XGBoostF-beta 分数F1分数公平感知机器学习福尔克斯-马洛斯指数Gap Statistic几何形态学青光眼生活质量-15 (Glaucoma Quality of Life-15)汉明损失惯性杰卡德指数提升和增益图LIME：局部可解释模型无关解释Log-Loss（交叉熵损失）纵向项目分析宏平均 F1平均绝对误差 (MAE)平均绝对百分比误差 (MAPE)平均绝对误差 (MASE)均方误差 (MSE)微平均F1分数模型校准归一化互信息精确率精确率-召回率曲线下面积价格公平量表R平方 (R²)召回率（灵敏度）稳健拉斯模型均方根误差 (RMSE)SHAP (SHapley Additive exPlanations)短问卷拉斯模型简式项目反应理论 (SF-IRT)轮廓系数特异度调查权重与校准对称平均绝对百分比误差 (sMAPE)令牌桶速率限制算法V-measure加权F1尤登J统计量