技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
sklearn-interface【数据与研究】Use AIF360's preferred sklearn-compatible pandas API for datasets, fairness metrics, scorers, estimators, and pipeline caveats.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when the task is best handled through the preferred aif360.sklearn API: pandas DataFrame/Series inputs, protected attributes stored in indexes, sklearn-compatible fairness metrics/scorers, estimators, meta-estimators, and pipeline caveats.
Reweighing, postprocessors, and PostProcessingMeta: use workflows and optional estimators.BinaryLabelDataset, StructuredDataset, StandardDataset, and legacy metric-class tasks to the sibling datasets-and-metrics sub-skill.aif360.algorithms preprocessing/inprocessing/postprocessing class workflows to the sibling mitigation-algorithms sub-skill.detectors-and-explainers sub-skill. This sub-skill only covers aif360.sklearn.metrics.mdss_bias_score as a metric helper.ot_distance as optional/unverified until the matching extra is installed and checked.