Metadata-Version: 2.1
Name: RCML
Version: 1.1.2
Summary: Minimal implementations of classical ML algorithms
Home-page: https://github.com/piyush01123/Revisiting-Classical-ML
Author: Piyush Singh
License: MIT License
        
        Copyright (c) 2022, Piyush Singh
        
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Description-Content-Type: text/markdown
License-File: LICENSE

# Revisiting Classsical ML
Implementations of classical ML algorithms in Numpy. Algorithms covered:
- Linear Regression
- Logistic Regression
- Support Vector Machines
- K Nearest Neighbours (both classifier and regressor)
- Naive Bayes
- K Means Clustering
- Decision Trees
- HMM

## Installation
```
pip install RCML
```

## Import classical ML algorithm implementations
```
# Classification models
from RCML import KNN_Classifier
from RCML import Decision_Tree
from RCML import Logistic_Regression
from RCML import SVM
from RCML import Naive_Bayes

# Clustering models
from RCML import KMeans
from RCML import KMeansPlusPlus

# Regression models
from RCML import KNN_Regressor 
from RCML import Linear_Regressor

# Sequence models
from RCML import viterbi as HMM
```

See examples of usage in the repo in files having prefix `run_*`
