pull request

README.md

@@ -25,6 +25,9 @@ can use `pip3 install -u 'numpy_ml[rl]'`.
 For more details on the available models, see the [project documentation](https://numpy-ml.readthedocs.io/).
 
 ## Available models
+<details>
+  <summary>Click to expand!</summary>
+
 1. **Gaussian mixture model**
     - EM training
 
@@ -92,6 +95,7 @@ For more details on the available models, see the [project documentation](https:
         - Leaky ReLU
         - ELU
         - SELU
+        - GELU
         - Exponential
         - Hard Sigmoid
         - Softplus
@@ -116,6 +120,9 @@ For more details on the available models, see the [project documentation](https:
     - Ridge regression
     - Logistic regression
     - Ordinary least squares
+    - Weighted linear regression
+    - Generalized linear model (log, logit, and identity link)
+    - Gaussian naive Bayes classifier
     - Bayesian linear regression w/ conjugate priors
         - Unknown mean, known variance (Gaussian prior)
         - Unknown mean, unknown variance (Normal-Gamma / Normal-Inverse-Wishart prior)
@@ -162,6 +169,7 @@ For more details on the available models, see the [project documentation](https:
     - Feature standardization
     - One-hot encoding / decoding
     - Huffman coding / decoding
+    - Byte pair encoding / decoding
     - Term frequency-inverse document frequency (TF-IDF) encoding
     - MFCC encoding
 
@@ -172,6 +180,7 @@ For more details on the available models, see the [project documentation](https:
     - Ball tree
     - Discrete sampler
     - Graph processing and generators
+</details>
 
 ## Contributing
 

docs/_static/css/custom.css

@@ -1,18 +1,32 @@
 body {
-    font-size: 16px !important;
+    font-size: 15px !important;
 }
 
-table.field-list,
-table.footnote {
+/* gray background for parameters */
+table.field-list {
     background-color: #f9f9f9 !important;
 }
 
+/* style the footnote display */
+table.footnote td {
+    padding: 0.3em 0.5em !important;
+    line-height: 1.4em !important;
+}
+
+table li {
+    padding-bottom: 0.5em;
+}
+
 table.field-list th,
 table.field-list td {
-    padding: 0.8em !important;
+    padding: 0.5em !important;
     border: 1px solid #888 !important;
 }
 
+p.rubric {
+    margin-top: 0px !important;
+}
+
 /* recolor the code snippets in sidebar */
 @media screen and (max-width: 875px) {
     div.sphinxsidebar h3,
@@ -24,6 +38,12 @@ table.field-list td {
     }
 }
 
+
+/* sidebar pinned to the top of the page */
+div.sphinxsidebar {
+    position: absolute;
+}
+
 /* don't show table delimiters */
 table.docutils {
     border: none !important;
@@ -36,7 +56,3 @@ table.docutils td, table.docutils th {
     border: none;
     padding: 0.0em 0.0em;
 }
-
-table.footnote td {
-    padding: 0.3em 0.5em;
-}

docs/conf.py

@@ -24,7 +24,7 @@
 # -- Project information -----------------------------------------------------
 
 project = "numpy-ml"
-copyright = "2020, David Bourgin"
+copyright = "2022, David Bourgin"
 author = "David Bourgin"
 
 # The short X.Y version

docs/numpy_ml.linear_models.lm.rst

@@ -37,3 +37,19 @@
 	:members:
 	:undoc-members:
 	:inherited-members:
+
+``GaussianNBClassifier``
+-----------------------------------------
+
+.. autoclass:: numpy_ml.linear_models.GaussianNBClassifier
+	:members:
+	:undoc-members:
+	:inherited-members:
+
+``GeneralizedLinearModel``
+-----------------------------------------
+
+.. autoclass:: numpy_ml.linear_models.GeneralizedLinearModel
+	:members:
+	:undoc-members:
+	:inherited-members: