From a875c6b2b49dd76e320d93fb1d6079ffe20d8564 Mon Sep 17 00:00:00 2001 From: KulikDM Date: Sun, 12 Nov 2023 12:03:37 +0200 Subject: [PATCH] Utilities doc update --- README.rst | 13 ++++++++++--- docs/index.rst | 13 ++++++++++--- 2 files changed, 20 insertions(+), 6 deletions(-) diff --git a/README.rst b/README.rst index d909422..b2beb51 100644 --- a/README.rst +++ b/README.rst @@ -278,9 +278,9 @@ Unsupervised Anomaly Detection. `_ | COMB | Thresholder Combination | None | `pythresh.thresholds.comb module `_ | +-----------+-------------------------------------------+--------------------+--------------------------------------------------------------------------------------------------------------------------------------------------------+ -****************************** - Implementations & Benchmarks -****************************** +****************************************** + Implementations, Benchmarks, & Utilities +****************************************** **The comparison among implemented models and general implementation** is made available below @@ -293,6 +293,13 @@ smallest uncertainty about its mean and is the most robust (best least accurate prediction). However, for interpretability and general performance the ``FILTER`` thresholder is a good fit. +Further utilities are available for assiting in the selection of the +most optimal outlier detection and thresholding methods `ranking +`_ as well as +determining the confidence with regards to the selected thresholding +method `thresholding confidence +`_ + ---- For Jupyter Notebooks, please navigate to `notebooks diff --git a/docs/index.rst b/docs/index.rst index 1556753..a974dfa 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -90,9 +90,9 @@ complex mathematical methods that involve graph theory and topology. ---- -************** - Benchmarking -************** +************************** + Benchmarking & Utilities +************************** Benchmarking has been done on all the thresholders and it was found that the ``META`` thresholder performed best while the ``CLF`` thresholder @@ -100,6 +100,13 @@ provided the smallest uncertainty about its mean and is the most robust (best least accurate prediction). However, for interpretability and general performance the ``FILTER`` thresholder is a good fit. +Further utilities are available for assiting in the selection of the +most optimal outlier detection and thresholding methods `ranking +`_ as well as +determining the confidence with regards to the selected thresholding +method `thresholding confidence +`_ + ---- ************************