Merge branch 'main' into tests

Author: trimmedjay

.github/labeler.yml

@@ -0,0 +1,26 @@
+# .github/labeler.yml
+
+# Label PRs touching C++ source files
+cpp:
+  - 'src/**/*.cpp'
+  - 'ml_library_include/**/*.h'
+  - 'ml_library_include/**/*.hpp'
+
+# Label PRs touching documentation
+docs:
+  - 'docs/**/*'
+  - '**/*.md'
+
+# Label PRs touching tests
+tests:
+  - 'tests/**/*'
+
+# Label PRs touching examples
+examples:
+  - 'examples/**/*'
+
+# Label PRs touching GitHub workflows
+ci:
+  - '.github/workflows/**/*'
+
+

.github/workflows/auto-label.yml

@@ -0,0 +1,27 @@
+# .github/workflows/auto-label.yml
+
+name: Auto-Label PRs and Issues
+
+on:
+  issues:
+    types: [opened]
+  pull_request:
+    types: [opened]
+
+permissions:
+  contents: read
+  issues: write
+  pull-requests: write
+
+jobs:
+  auto-label:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v3
+
+    - name: Auto-label
+      uses: actions/labeler@v3
+      with:
+        repo-token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/doxygen.yml

@@ -16,9 +16,17 @@ jobs:
     - name: Checkout code
       uses: actions/checkout@v3 
 
+    - name: Install Dependencies
+      run: |
+        sudo apt-get update
+        sudo apt-get install -y wget
+
     - name: Install Doxygen
       run: sudo apt-get install -y doxygen
 
+    - name: Create Output Directory
+      run: mkdir -p docs/doxygen
+
     - name: Generate Documentation
       run: doxygen Doxyfile
 

.gitignore

@@ -17,8 +17,7 @@ cmake_install.cmake
 Makefile
 
 # Doxygen Output
-docs/doxygen/
-
+docs/
 # Generated binaries and object files
 *.obj
 *.o

Doxyfile

@@ -348,7 +348,7 @@ OPTIMIZE_OUTPUT_SLICE  = NO
 #
 # Note see also the list of default file extension mappings.
 
-EXTENSION_MAPPING      = md=markdown
+EXTENSION_MAPPING = md=markdown
 
 # If the MARKDOWN_SUPPORT tag is enabled then doxygen pre-processes all comments
 # according to the Markdown format, which allows for more readable
@@ -358,7 +358,7 @@ EXTENSION_MAPPING      = md=markdown
 # case of backward compatibilities issues.
 # The default value is: YES.
 
-MARKDOWN_SUPPORT       = YES
+MARKDOWN_SUPPORT = YES
 
 # When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up
 # to that level are automatically included in the table of contents, even if
@@ -402,7 +402,7 @@ BUILTIN_STL_SUPPORT    = NO
 # enable parsing support.
 # The default value is: NO.
 
-CPP_CLI_SUPPORT        = NO
+CPP_CLI_SUPPORT        = YES
 
 # Set the SIP_SUPPORT tag to YES if your project consists of sip (see:
 # https://www.riverbankcomputing.com/software/sip/intro) sources only. Doxygen
@@ -635,7 +635,7 @@ INTERNAL_DOCS          = NO
 # Possible values are: SYSTEM, NO and YES.
 # The default value is: SYSTEM.
 
-CASE_SENSE_NAMES       = SYSTEM
+CASE_SENSE_NAMES       = YES
 
 # If the HIDE_SCOPE_NAMES tag is set to NO then doxygen will show members with
 # their full class and namespace scopes in the documentation. If set to YES, the

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 Jide Oyelayo
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -10,8 +10,7 @@
 
 ```plaintext
 cpp-ml-library/
-├── include/                # Header files
-├── src/                    # Source files
+├── ml_library_include/     # Header files
 ├── tests/                  # Unit tests
 ├── examples/               # Example usage files
 ├── docs/                   # Documentation files
@@ -50,33 +49,33 @@ make install
 To use this library in your C++ project, include the master header file:
 
 ```cpp
-#include "ml/ml.h"
+#include "ml_library_include/ml.h"
 ```
 
 ## Implemented Algorithms
 
 The following machine learning algorithms are planned, inspired by concepts and techniques taught in the Udemy course:
 
 1. **Regression**
-   - [x] Polynomial Regression
-   - [x] Multi-Linear Regression
-   - [x] Logistic Regression
-   - [x] Decision Tree Regression
-   - [x] Random Forest Regression
-   - [x] K-Nearest Neighbors
+   - [x] Polynomial Regression (PolynomialRegression)
+   - [x] Multi-Linear Regression (MultilinearRegression)
+   - [x] Logistic Regression (LogisticRegression)
+   - [x] Decision Tree Regression (DecisionTreeRegressor)
+   - [x] Random Forest Regression (RandomForestRegressor)
+   - [x] K-Nearest Neighbors (KNNRegressor)
 
 
 2. **Classification**
-   - [x] Decision Tree Classifier
-   - [x] Random Forest Classifier
-   - [x] K-Nearest Neighbors
+   - [x] Decision Tree Classifier (DecisionTreeClassifier)
+   - [x] Random Forest Classifier (RandomForestClassifier)
+   - [x] K-Nearest Neighbors (KNNClassifier)
 
 3. **Clustering**
-   - [x] K-Means Clustering
-   - [x] Hierarchical clustering
+   - [x] K-Means Clustering (KMeans)
+   - [x] Hierarchical clustering (HierarchicalClustering)
 
 4. **Neural Networks**
-   - [x] Neural Network (NN)
+   - [x] Neural Network (NeuralNetwork)
    - [ ] Artificial Neural Network (ANN)
    - [ ] Convolutional Neural Network (CNN)
 
@@ -85,27 +84,30 @@ The following machine learning algorithms are planned, inspired by concepts and
    - [x] Eclat
 
 6. **Support Vector Machine**
-   - [ ] Support Vector Regression (SVR)
+   - [ ] Support Vector Regression (SupportVectorRegression)
 
 ## Algorithm Implementation Progress
 
 | Algorithm Category       | Algorithm                    | Implemented | Tests | Examples |
 |--------------------------|------------------------------|-------------|-------|----------|
-| **Regression**           | Polynomial Regression        | [x]         | [ ]   | [x]      |
-|                          | Logistic Regression      | [x]         | [ ]   | [x]      |
-|                          | Multi-Linear Regression      | [x]         | [ ]   | [x]      |
-|                          | Decision Tree Regression     | [x]         | [ ]   | [ ]      |
-|                          | Random Forest Regression     | [x]         | [ ]   | [ ]      |
-| **Classification**       | Decision Tree Classifier     | [x]         | [ ]   | [ ]      |
-|                          | Random Forest Classifier     | [x]         | [ ]   | [ ]      |
-|                          | K-Nearest Neighbors          | [x]         | [ ]   | [ ]      |
-| **Clustering**           | K-Means Clustering           | [x]         | [ ]   | [ ]      |
-| **Neural Networks**      | Neural Network (NN)          | [x]         | [x]   | [x]      |
+| **Regression**           | Polynomial Regression (PolynomialRegression)        | [x]         | [ ]   | [x]      |
+|                          | Logistic Regression (LogisticRegression)     | [x]         | [ ]   | [x]      |
+|                          | Multi-Linear Regression (MultilinearRegression)      | [x]         | [ ]   | [x]      |
+|                          | Decision Tree Regression (DecisionTreeRegressor)     | [ ]         | [ ]   | [ ]      |
+|                          | Random Forest Regression (RandomForestRegressor)     | [ ]         | [ ]   | [ ]      |
+|                          | K-Nearest Neighbors (KNNRegressor)          | [x]         | [ ]   | [ ]      |
+| **Classification**       | Decision Tree Classifier (DecisionTreeClassifier)    | [ ]         | [ ]   | [ ]      |
+|                          | Random Forest Classifier (RandomForestClassifier)    | [ ]         | [ ]   | [ ]      |
+|                          | K-Nearest Neighbors (KNNClassifier)          | [x]         | [ ]   | [ ]      |
+| **Clustering**           | K-Means Clustering (KMeans)           | [x]         | [ ]   | [ ]      |
+|                          | Hierarchical clustering (HierarchicalClustering)          | [x]         | [ ]   | [ ]      |
+| **Neural Networks**      | Neural Network (NeuralNetwork)          | [x]         | [x]   | [x]      |
 |                          | Artificial Neural Network    | [ ]         | [ ]   | [ ]      |
 |                          | Convolutional Neural Network | [ ]         | [ ]   | [ ]      |
-| **Association Rule Learning** | Apriori                | [x]         | [ ]   | [x]      |
-|                          | Eclat                        | [x]         | [ ]   | [x]      |
-| **Support Vector Machine** | Support Vector Regression (SVR) | [ ]    | [ ]   | [ ]      |
+| **Association Rule Learning** | Apriori                | [x]         | [x]   | [x]      |
+|                          | Eclat                        | [x]         | [x]   | [x]      |
+| **Support Vector Machine** | Support Vector Regression (SupportVectorRegression) | [ ]    | [ ]   | [ ]      |
+
 
 
 
@@ -135,7 +137,7 @@ int main() {
 
 ## Documentation
 
-The documentation for this project is generated using Doxygen and is available online at [GitHub Pages](https://jideoyelayo1.github.io/cpp-ml-library/). The documentation provides details on each class, function, and algorithm.
+The documentation for this project is generated using Doxygen and is available online at [GitHub Pages](https://jideoyelayo.com/cpp-ml-library/). The documentation provides details on each class, function, and algorithm.
 
 ## Contributing