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Minimal implementations of classical ML algorithms

Project description

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_*

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