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_*