用法:
explain(anomaly, scaled=True)
根據直方圖中每個特征的貢獻(t-scores)解釋異常。
- anomaly:(
cupy.ndarray
) - 從輸入數據集中選擇的異常 - scaled:(
boolean
) - 設置為縮放輸出特征重要性分數
- anomaly:(
參數:
例子:
>>> loda_ad.explain(x[5]) # x[5] is found anomaly array([[1. ], [0. ], [0.69850349], [0.91081035], [0.78774349]])
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注:本文由純淨天空篩選整理自rapids.ai大神的英文原創作品 clx.analytics.loda.Loda.explain。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。