Machine Learning Repository

Mosty written using Jupyter Notebook

Algorithm Implementations

KNN - The KNN file knnAlgorithm.py reads from a .arff file, calculates k-means neighbor. It can be adapted to fit any type of data.

Name		Name	Last commit message	Last commit date
Latest commit History 48 Commits
data		data
.gitignore		.gitignore
HW2_DataSplit.py		HW2_DataSplit.py
LICENSE		LICENSE
README.md		README.md
bonus_dectree.py		bonus_dectree.py
bonus_randforest.py		bonus_randforest.py
componentAnalysis.py		componentAnalysis.py
dataframe_kmeans.py		dataframe_kmeans.py
dm_clustering.py		dm_clustering.py
dtw.py		dtw.py
featureSelection_LOOCV.py		featureSelection_LOOCV.py
gaussianBayes.py		gaussianBayes.py
gramSchmidtnorm.py		gramSchmidtnorm.py
hw1data.mat		hw1data.mat
hw1dataQ8.mat		hw1dataQ8.mat
hw2data.mat		hw2data.mat
knnAlgorithm.py		knnAlgorithm.py
lab2_kmeans.py		lab2_kmeans.py
mapper.py		mapper.py
matrixMult.js		matrixMult.js
ml_kmeans.py		ml_kmeans.py
pdfs.py		pdfs.py
q3_adults.py		q3_adults.py
reducer.py		reducer.py
results.arff		results.arff
ridgeRegression.py		ridgeRegression.py
sigmoid.py		sigmoid.py
simpleClassifiers.py		simpleClassifiers.py
svm.py		svm.py
test-file.txt		test-file.txt
test-regex.py		test-regex.py
test.arff		test.arff
test.sh		test.sh
testDF.sh		testDF.sh
testDT.sh		testDT.sh
testML.sh		testML.sh
testQ3.sh		testQ3.sh
testRF.sh		testRF.sh
train.arff		train.arff
vae.ipynb		vae.ipynb