forked from JointCloud/JCC-DeepOD
doc init
This commit is contained in:
xuhongzuo
parent
5942ef5d6a
commit
59d2d752f1
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# Read the Docs configuration file for Sphinx projects
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# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
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# Required
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version: 2
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# Set the OS, Python version and other tools you might need
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build:
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os: ubuntu-22.04
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tools:
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python: "3.12"
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# You can also specify other tool versions:
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# nodejs: "20"
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# rust: "1.70"
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# golang: "1.20"
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# Build documentation in the "docs/" directory with Sphinx
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sphinx:
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configuration: docs/conf.py
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# You can configure Sphinx to use a different builder, for instance use the dirhtml builder for simpler URLs
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# builder: "dirhtml"
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# Fail on all warnings to avoid broken references
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# fail_on_warning: true
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# Optionally build your docs in additional formats such as PDF and ePub
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# formats:
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# - pdf
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# - epub
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# Optional but recommended, declare the Python requirements required
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# to build your documentation
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# See https://docs.readthedocs.io/en/stable/guides/reproducible-builds.html
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# python:
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# install:
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# - requirements: docs/requirements.txt
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@ -0,0 +1,171 @@
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# -*- coding: utf-8 -*-
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#
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# Configuration file for the Sphinx documentation builder.
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#
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# This file does only contain a selection of the most common options. For a
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# full list see the documentation:
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# http://www.sphinx-doc.org/en/master/config
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# -- Path setup --------------------------------------------------------------
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# If extensions (or modules to document with autodoc) are in another directory,
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# add these directories to sys.path here. If the directory is relative to the
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# documentation root, use os.path.abspath to make it absolute, like shown here.
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#
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import os
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import sys
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from os.path import dirname, abspath
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sys.path.insert(0, abspath('..'))
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deepod_dir = dirname(dirname(abspath(__file__)))
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version_path = os.path.join(deepod_dir, 'deepod', 'version.py')
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exec(open(version_path).read())
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# -- Project information -----------------------------------------------------
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project = 'deepod'
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copyright = '2023, Hongzuo Xu'
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author = 'Hongzuo Xu'
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# -- General configuration ---------------------------------------------------
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# If your documentation needs a minimal Sphinx version, state it here.
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#
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# needs_sphinx = '1.0'
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# Add any Sphinx extension module names here, as strings. They can be
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# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
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# ones.
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extensions = [
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'sphinx.ext.autodoc',
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'sphinx.ext.doctest',
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'sphinx.ext.intersphinx',
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'sphinx.ext.coverage',
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'sphinx.ext.imgmath',
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'sphinx.ext.viewcode',
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'sphinxcontrib.bibtex',
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# 'sphinx.ext.napoleon',
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# 'sphinx_rtd_theme',
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]
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bibtex_bibfiles = ['zreferences.bib']
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# Add any paths that contain templates here, relative to this directory.
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templates_path = ['_templates']
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# The suffix(es) of source filenames.
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# You can specify multiple suffix as a list of string:
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#
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source_suffix = ['.rst', '.md']
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# The master toctree document.
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master_doc = 'index'
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# The language for content autogenerated by Sphinx. Refer to documentation
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# for a list of supported languages.
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#
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# This is also used if you do content translation via gettext catalogs.
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# Usually you set "language" from the command line for these cases.
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language = None
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# List of patterns, relative to source directory, that match files and
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# directories to ignore when looking for source files.
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# This pattern also affects html_static_path and html_extra_path .
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exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store', 'pyod.test.rst']
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# The name of the Pygments (syntax highlighting) style to use.
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pygments_style = 'sphinx'
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# -- Options for HTML output -------------------------------------------------
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# The theme to use for HTML and HTML Help pages. See the documentation for
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# a list of builtin themes.
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#
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# html_theme = 'default'
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html_theme = "furo"
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# Theme options are theme-specific and customize the look and feel of a theme
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# further. For a list of options available for each theme, see the
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# documentation.
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#
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# html_theme_options = {}
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,
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# so a file named "default.css" will overwrite the builtin "default.css".
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html_static_path = ['_static']
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# Custom sidebar templates, must be a dictionary that maps document names
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# to template names.
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#
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# The default sidebars (for documents that don't match any pattern) are
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# defined by theme itself. Builtin themes are using these templates by
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# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
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# 'searchbox.html']``.
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#
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# html_sidebars = {}
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# html_sidebars = {'**': ['globaltoc.html', 'relations.html', 'sourcelink.html',
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# 'searchbox.html']}
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# -- Options for HTMLHelp output ---------------------------------------------
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# Output file base name for HTML help builder.
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htmlhelp_basename = 'deepoddoc'
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# -- Options for LaTeX output ------------------------------------------------
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latex_elements = {
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# The paper size ('letterpaper' or 'a4paper').
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#
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# 'papersize': 'letterpaper',
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# The font size ('10pt', '11pt' or '12pt').
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#
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# 'pointsize': '10pt',
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# Additional stuff for the LaTeX preamble.
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#
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# 'preamble': '',
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# Latex figure (float) alignment
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#
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# 'figure_align': 'htbp',
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}
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# Grouping the document tree_ into LaTeX files. List of tuples
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# (source start file, target name, title,
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# author, documentclass [howto, manual, or own class]).
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latex_documents = [
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(master_doc, 'deepod.tex', 'deepod Documentation',
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'Hongzuo Xu', 'manual'),
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]
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# -- Options for manual page output ------------------------------------------
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# One entry per manual page. List of tuples
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# (source start file, name, description, authors, manual section).
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man_pages = [
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(master_doc, 'pyod', 'pyod Documentation',
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[author], 1)
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]
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# -- Options for Texinfo output ----------------------------------------------
|
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|
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# Grouping the document tree_ into Texinfo files. List of tuples
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# (source start file, target name, title, author,
|
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# dir menu entry, description, category)
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texinfo_documents = [
|
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(master_doc, 'DeepOD', 'DeepOD Documentation',
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author, 'DeepOD', 'One line description of project.',
|
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'Miscellaneous'),
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]
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# -- Extension configuration -------------------------------------------------
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|
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# -- Options for intersphinx extension ---------------------------------------
|
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|
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# Example configuration for intersphinx: refer to the Python standard library.
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intersphinx_mapping = {'https://docs.python.org/': None}
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|
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@ -0,0 +1,503 @@
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|||
@inproceedings{liu2008isolation,
|
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title={Isolation forest},
|
||||
author={Liu, Fei Tony and Ting, Kai Ming and Zhou, Zhi-Hua},
|
||||
booktitle={Data Mining, 2008. ICDM'08. Eighth IEEE International Conference on},
|
||||
pages={413--422},
|
||||
year={2008},
|
||||
organization={IEEE}
|
||||
}
|
||||
|
||||
@article{liu2012isolation,
|
||||
title={Isolation-based anomaly detection},
|
||||
author={Liu, Fei Tony and Ting, Kai Ming and Zhou, Zhi-Hua},
|
||||
journal={ACM Transactions on Knowledge Discovery from Data (TKDD)},
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||||
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pages={3},
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year={2012},
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publisher={ACM}
|
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}
|
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|
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@inproceedings{kriegel2011interpreting,
|
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title={Interpreting and unifying outlier scores},
|
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author={Kriegel, Hans-Peter and Kroger, Peer and Schubert, Erich and Zimek, Arthur},
|
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|
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}
|
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|
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@article{aggarwal2015theoretical,
|
||||
title={Theoretical foundations and algorithms for outlier ensembles},
|
||||
author={Aggarwal, Charu C and Sathe, Saket},
|
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journal={ACM SIGKDD Explorations Newsletter},
|
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|
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|
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}
|
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|
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@inproceedings{ramaswamy2000efficient,
|
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title={Efficient algorithms for mining outliers from large data sets},
|
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author={Ramaswamy, Sridhar and Rastogi, Rajeev and Shim, Kyuseok},
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|
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|
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|
||||
@inproceedings{angiulli2002fast,
|
||||
title={Fast outlier detection in high dimensional spaces},
|
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author={Angiulli, Fabrizio and Pizzuti, Clara},
|
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|
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|
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|
||||
@inproceedings{kriegel2008angle,
|
||||
title={Angle-based outlier detection in high-dimensional data},
|
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|
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booktitle={Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining},
|
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|
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|
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|
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|
||||
@inproceedings{lazarevic2005feature,
|
||||
title={Feature bagging for outlier detection},
|
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author={Lazarevic, Aleksandar and Kumar, Vipin},
|
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|
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|
||||
}
|
||||
|
||||
@article{goldstein2012histogram,
|
||||
title={Histogram-based outlier score (hbos): A fast unsupervised anomaly detection algorithm},
|
||||
author={Goldstein, Markus and Dengel, Andreas},
|
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journal={KI-2012: Poster and Demo Track},
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pages={59--63},
|
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year={2012},
|
||||
publisher={Citeseer}
|
||||
}
|
||||
|
||||
@techreport{shyu2003novel,
|
||||
title={A novel anomaly detection scheme based on principal component classifier},
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|
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year={2003},
|
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institution={MIAMI UNIV CORAL GABLES FL DEPT OF ELECTRICAL AND COMPUTER ENGINEERING}
|
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}
|
||||
|
||||
@inproceedings{aggarwal2015outlier,
|
||||
title={Outlier analysis},
|
||||
author={Aggarwal, Charu C},
|
||||
booktitle={Data mining},
|
||||
pages={75--79},
|
||||
year={2015},
|
||||
organization={Springer}
|
||||
}
|
||||
|
||||
@inproceedings{breunig2000lof,
|
||||
title={LOF: identifying density-based local outliers},
|
||||
author={Breunig, Markus M and Kriegel, Hans-Peter and Ng, Raymond T and Sander, J{\"o}rg},
|
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booktitle={ACM sigmod record},
|
||||
volume={29},
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|
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pages={93--104},
|
||||
year={2000},
|
||||
organization={ACM}
|
||||
}
|
||||
|
||||
|
||||
@inproceedings{zhao2018xgbod,
|
||||
title={XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning},
|
||||
author={Zhao, Yue and Hryniewicki, Maciej K},
|
||||
booktitle={International Joint Conference on Neural Networks (IJCNN)},
|
||||
year={2018},
|
||||
organization={IEEE}
|
||||
}
|
||||
|
||||
@article{rousseeuw1999fast,
|
||||
title={A fast algorithm for the minimum covariance determinant estimator},
|
||||
author={Rousseeuw, Peter J and Driessen, Katrien Van},
|
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|
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|
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|
||||
|
||||
@article{hardin2004outlier,
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||||
title={Outlier detection in the multiple cluster setting using the minimum covariance determinant estimator},
|
||||
author={Hardin, Johanna and Rocke, David M},
|
||||
journal={Computational Statistics \& Data Analysis},
|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
|
||||
@article{he2003discovering,
|
||||
title={Discovering cluster-based local outliers},
|
||||
author={He, Zengyou and Xu, Xiaofei and Deng, Shengchun},
|
||||
journal={Pattern Recognition Letters},
|
||||
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|
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|
||||
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|
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|
||||
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|
||||
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|
||||
|
||||
@inproceedings{zhao2018dcso,
|
||||
title={DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles},
|
||||
author={Yue Zhao and Maciej K. Hryniewicki},
|
||||
booktitle={ACM SIGKDD Workshop on Outlier Detection De-constructed (ODD v5.0)},
|
||||
year={2018},
|
||||
organization={ACM}
|
||||
}
|
||||
|
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@techreport{janssens2012stochastic,
|
||||
title={Stochastic outlier selection},
|
||||
author={Janssens, JHM and Husz{\'a}r, Ferenc and Postma, EO and van den Herik, HJ},
|
||||
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|
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|
||||
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|
||||
|
||||
@inproceedings{papadimitriou2003loci,
|
||||
title={LOCI: Fast outlier detection using the local correlation integral},
|
||||
author={Papadimitriou, Spiros and Kitagawa, Hiroyuki and Gibbons, Phillip B and Faloutsos, Christos},
|
||||
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|
||||
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|
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|
||||
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|
||||
}
|
||||
|
||||
@inproceedings{zhao2019lscp,
|
||||
title={{LSCP:} Locally Selective Combination in Parallel Outlier Ensembles},
|
||||
author={Zhao, Yue and Nasrullah, Zain and Hryniewicki, Maciej K and Li, Zheng},
|
||||
booktitle={Proceedings of the 2019 {SIAM} International Conference on Data Mining, {SDM} 2019},
|
||||
pages={585--593},
|
||||
month = {May},
|
||||
year={2019},
|
||||
address = {Calgary, Canada},
|
||||
organization={SIAM},
|
||||
url={https://doi.org/10.1137/1.9781611975673.66},
|
||||
doi={10.1137/1.9781611975673.66}
|
||||
}
|
||||
|
||||
@article{liu2019generative,
|
||||
title={Generative adversarial active learning for unsupervised outlier detection},
|
||||
author={Liu, Yezheng and Li, Zhe and Zhou, Chong and Jiang, Yuanchun and Sun, Jianshan and Wang, Meng and He, Xiangnan},
|
||||
journal={IEEE Transactions on Knowledge and Data Engineering},
|
||||
year={2019},
|
||||
publisher={IEEE}
|
||||
}
|
||||
|
||||
@article{zhao2019pyod,
|
||||
title={{PyOD}: A python toolbox for scalable outlier detection},
|
||||
author={Zhao, Yue and Nasrullah, Zain and Li, Zheng},
|
||||
journal={Journal of Machine Learning Research},
|
||||
volume={20},
|
||||
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|
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|
||||
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|
||||
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|
||||
|
||||
@article{ramakrishnan2019anomaly,
|
||||
title={Anomaly Detection for an E-commerce Pricing System},
|
||||
author={Ramakrishnan, Jagdish and Shaabani, Elham and Li, Chao and Sustik, M{\'a}ty{\'a}s A},
|
||||
journal={arXiv preprint arXiv:1902.09566},
|
||||
year={2019}
|
||||
}
|
||||
|
||||
@inproceedings{kalayci2018anomaly,
|
||||
title={Anomaly Detection in Wireless Sensor Networks Data by Using Histogram Based Outlier Score Method},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
organization={IEEE}
|
||||
}
|
||||
|
||||
@article{scholkopf2001estimating,
|
||||
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|
||||
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|
||||
journal={Neural computation},
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||||
volume={13},
|
||||
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|
||||
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|
||||
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|
||||
publisher={MIT Press}
|
||||
}
|
||||
|
||||
@inproceedings{tang2002enhancing,
|
||||
title={Enhancing effectiveness of outlier detections for low density patterns},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
organization={Springer}
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||||
}
|
||||
|
||||
@article{krishnan2019alphaclean,
|
||||
title={AlphaClean: Automatic Generation of Data Cleaning Pipelines},
|
||||
author={Krishnan, Sanjay and Wu, Eugene},
|
||||
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|
||||
year={2019}
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||||
}
|
||||
|
||||
@inproceedings{kriegel2009outlier,
|
||||
title={Outlier detection in axis-parallel subspaces of high dimensional data},
|
||||
author={Kriegel, Hans-Peter and Kr{\"o}ger, Peer and Schubert, Erich and Zimek, Arthur},
|
||||
booktitle={Pacific-Asia Conference on Knowledge Discovery and Data Mining},
|
||||
pages={831--838},
|
||||
year={2009},
|
||||
organization={Springer}
|
||||
}
|
||||
|
||||
@inproceedings{li2019mad,
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||||
title={MAD-GAN: Multivariate anomaly detection for time series data with generative adversarial networks},
|
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Reference in New Issue