https://github.com/parvvaresh/ml-algorithms

Here we have fully implemented a number of algorithms related to machine learning
https://github.com/parvvaresh/ml-algorithms

cosine-similarity decision-tree knn-classification linear-regression logstic-regression naive-bayes-classifier pca pca-analysis random-forest svm-classifier

Last synced: 4 months ago
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Here we have fully implemented a number of algorithms related to machine learning

• Host: GitHub
• URL: https://github.com/parvvaresh/ml-algorithms
• Owner: parvvaresh
• Created: 2023-03-21T15:35:51.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-08-10T17:09:48.000Z (11 months ago)
• Last Synced: 2024-08-10T20:37:06.947Z (11 months ago)
• Topics: cosine-similarity, decision-tree, knn-classification, linear-regression, logstic-regression, naive-bayes-classifier, pca, pca-analysis, random-forest, svm-classifier
• Language: Python
• Homepage:
• Size: 392 KB
• Stars: 19
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
### 1. Regression:

- linear model 

    - Linear Regression ✓

    - Ridge Regression ✓

    - Lasso Regression ✓

    - ElasticNet Regression ✓

- KNN Regression (with 2 distance metric) ✓

    - uniform KNN ✓

    - distance Weight KNN ✓

- Tree Regression

    - Decision Tree Regression

    - Random Forest Regression

- Support Vector Regression (SVR)

### 2. Clustering:

- K-Means

- Hierarchical Clustering

- DBSCAN

- Mean Shift Clustering

### 3. Classification:

- KNN (with 2 distance metric) ✓

    - uniform KNN ✓

    - distance Weight KNN ✓

- Tree 

    - Decision Tree ✓

    - Random Forest ✓

- Ensemble

    - AdaBost ✓

- Regression : 

    - Logistic Regression ✓

    - Ridge Regression 

    - Lasso Regression 

    - ElasticNet Regression 

- Bayesian 

    - Gaussian ✓

    - Multinomial ✓

- Minimum Distance Classifier ✓

- Support Vector Machine (SVM)

- Perceptron ✓

### 3. Dimensionality Reduction:

- Principal Component Analysis (PCA)

- Linear Discriminant Analysis (LDA)

### 4. Normalization data

- sandardScaler ✓

- MinMaxScaler ✓

- MaxAbsScaler ✓

- RobustScaler ✓

- Normalizer ✓

### 5. metrics 

- regression : 

    - MSE ✓

    - MAE ✓

    - R2-Score ✓

- Classification:

    - accourcy ✓

    - recall ✓

    - prescion ✓

    - f1-score ✓

### 6.cosine similarity 

- cosine similarity ✓

- cosine similarity matrix ✓

### 7. Statistics

- covariance

- covariance matrix

- correlation