用法:
score(input_data)
使用 n_random_cuts 直方圖的負似然計算異常分數。
input_data:(
cupy.ndarray
) - NxD 訓練樣本
參數:
例子:
>>> from clx.analytics.loda import Loda >>> import cupy as cp >>> x = cp.random.randn(100,5) # 5-D multivariate synthetic dataset >>> loda_ad = Loda(n_bins=None, n_random_cuts=100) >>> loda_ad.fit(x) >>> loda_ad.score(x) array([0.04295848, 0.02853553, 0.04587308, 0.03750692, 0.05050418, 0.02671958, 0.03538646, 0.05606504, 0.03418612, 0.04040502, 0.03542846, 0.02801463, 0.04884918, 0.02943411, 0.02741364, 0.02702433, 0.03064191, 0.02575712, 0.03957355, 0.02729784, ... 0.03943715, 0.02701243, 0.02880341, 0.04086408, 0.04365477])
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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.score。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。