Merge pull request #145 from lahovniktadej/main

Documentation

docs/requirements.txt

@@ -1,133 +1,10 @@
-#
-# This file is autogenerated by pip-compile with Python 3.11
-# by the following command:
-#
-#    pip-compile
-#
-alabaster==0.7.13
-    # via sphinx
-babel==2.13.1
-    # via sphinx
-certifi==2024.7.4
-    # via requests
-charset-normalizer==3.3.1
-    # via requests
-click==8.1.7
-    # via nltk
-contourpy==1.2.0
-    # via matplotlib
-cycler==0.12.1
-    # via matplotlib
-docutils==0.18.1
-    # via
-    #   pybtex-docutils
-    #   sphinx
-    #   sphinx-rtd-theme
-    #   sphinxcontrib-bibtex
-et-xmlfile==1.1.0
-    # via openpyxl
-fonttools==4.48.1
-    # via matplotlib
-idna==3.7
-    # via requests
-imagesize==1.4.1
-    # via sphinx
-jinja2==3.1.5
-    # via sphinx
-joblib==1.3.2
-    # via nltk
-kiwisolver==1.4.5
-    # via matplotlib
-latexcodec==2.0.1
-    # via pybtex
-markupsafe==2.1.3
-    # via jinja2
-matplotlib==3.8.2
-    # via niapy
-niapy==2.1.0
-    # via -r requirements.in
-nltk==3.9
-    # via -r requirements.in
-numpy==1.26.4
-    # via
-    #   -r requirements.in
-    #   contourpy
-    #   matplotlib
-    #   niapy
-    #   pandas
-openpyxl==3.1.2
-    # via niapy
-packaging==23.2
-    # via
-    #   matplotlib
-    #   sphinx
-pandas==2.2.0
-    # via
-    #   -r requirements.in
-    #   niapy
-pillow==10.3.0
-    # via matplotlib
-pybtex==0.24.0
-    # via
-    #   pybtex-docutils
-    #   sphinxcontrib-bibtex
-pybtex-docutils==1.0.3
-    # via sphinxcontrib-bibtex
-pygments==2.16.1
-    # via sphinx
-pyparsing==3.1.1
-    # via matplotlib
-python-dateutil==2.8.2
-    # via
-    #   matplotlib
-    #   pandas
-pytz==2024.1
-    # via pandas
-pyyaml==6.0.1
-    # via pybtex
-regex==2023.12.25
-    # via nltk
-requests==2.32.0
-    # via sphinx
-six==1.16.0
-    # via
-    #   latexcodec
-    #   pybtex
-    #   python-dateutil
-snowballstemmer==2.2.0
-    # via sphinx
-sphinx==7.2.6
-    # via
-    #   -r requirements.in
-    #   sphinx-rtd-theme
-    #   sphinxcontrib-applehelp
-    #   sphinxcontrib-bibtex
-    #   sphinxcontrib-devhelp
-    #   sphinxcontrib-htmlhelp
-    #   sphinxcontrib-jquery
-    #   sphinxcontrib-qthelp
-    #   sphinxcontrib-serializinghtml
-sphinx-rtd-theme==1.3.0
-    # via -r requirements.in
-sphinxcontrib-applehelp==1.0.7
-    # via sphinx
-sphinxcontrib-bibtex==2.5.0
-    # via -r requirements.in
-sphinxcontrib-devhelp==1.0.5
-    # via sphinx
-sphinxcontrib-htmlhelp==2.0.4
-    # via sphinx
-sphinxcontrib-jquery==4.1
-    # via sphinx-rtd-theme
-sphinxcontrib-jsmath==1.0.1
-    # via sphinx
-sphinxcontrib-qthelp==1.0.6
-    # via sphinx
-sphinxcontrib-serializinghtml==1.1.9
-    # via sphinx
-tqdm==4.66.3
-    # via nltk
-tzdata==2023.4
-    # via pandas
-urllib3==2.2.2
-    # via requests
+niapy>=2.5.2,<3.0.0
+numpy>=1.26.1,<2.0.0
+pandas>=2.1.1,<3.0.0
+nltk>=3.8.1,<4.0.0
+plotly>=5.22.0,<6.0.0
+scikit-learn>=1.5.1,<2.0.0
+sphinx-rtd-theme>=1.0.0,<2.0.0
+sphinxcontrib-bibtex>=2.4.1,<3.0.0
+sphinx>=7.2.6,<8.0.0
+tomli>=2.0.1,<3.0.0; python_version < "3.11"

niaarm/rule.py

@@ -159,13 +159,13 @@ class Rule:
         leverage: difference between the frequency of antecedent and the consequent appearing together and the expected
         frequency of them appearing separately based on their individual support
 
-        :math: `leverage(X \implies Y) = support(X \implies Y) - (support(X) \times support(Y))`
+         :math:`leverage(X \implies Y) = support(X \implies Y) - (support(X) \times support(Y))`
 
-        **Range:** :math: `[-1, 1]` (-1 reflects total negative association, 1 reflects perfect positive association
+         **Range:** :math:`[-1, 1]` (-1 reflects total negative association, 1 reflects perfect positive association
          and 0 reflects independence)
 
-        **Reference:** Gregory Piatetsky-Shapiro. 1991. Discovery, Analysis, and Presentation of Strong Rules. In
-        Knowledge Discovery in Databases, Gregory Piatetsky-Shapiro and William J. Frawley (Eds.). AAAI/MIT Press, 229–248.
+         **Reference:** Gregory Piatetsky-Shapiro. 1991. Discovery, Analysis, and Presentation of Strong Rules. In
+         Knowledge Discovery in Databases, Gregory Piatetsky-Shapiro and William J. Frawley (Eds.). AAAI/MIT Press, 229–248.
     """
 
     __slots__ = (