GitHub - ronitshaw/CSE-291-Pattern-Recognition-Machine-Learning

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Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
Images		Images
CSE 291_HW2_RF_MNIST.ipynb		CSE 291_HW2_RF_MNIST.ipynb
CSE 291_HW3 COVER KNN .ipynb		CSE 291_HW3 COVER KNN .ipynb
CSE 291_HW3 MNIST KNN .ipynb		CSE 291_HW3 MNIST KNN .ipynb
CSE_291_HW_2_COVER_RF.ipynb		CSE_291_HW_2_COVER_RF.ipynb
HW 1- Pattern Recognition.docx		HW 1- Pattern Recognition.docx
HW2.pdf		HW2.pdf
NB_MNIST.ipynb		NB_MNIST.ipynb
NB_Wine.ipynb		NB_Wine.ipynb
PCA_LDA_NB_MNIST.ipynb		PCA_LDA_NB_MNIST.ipynb
PCA_LDA_NB_Wine.ipynb		PCA_LDA_NB_Wine.ipynb
PCA_MNIST-trying with scalling and adding LDA.ipynb		PCA_MNIST-trying with scalling and adding LDA.ipynb
PCA_MNIST-trying with scalling.ipynb		PCA_MNIST-trying with scalling.ipynb
PCA_MNIST.ipynb		PCA_MNIST.ipynb
PCA_NB_MNIST.ipynb		PCA_NB_MNIST.ipynb
PCA_NB_Wine.ipynb		PCA_NB_Wine.ipynb
PCA_Wine_Data_Set.ipynb		PCA_Wine_Data_Set.ipynb
PCA_Wine_Data_Set_LDA.ipynb		PCA_Wine_Data_Set_LDA.ipynb
README		README
README~		README~
test.csv		test.csv
train.csv		train.csv
wine.data.txt		wine.data.txt

Repository files navigation

Homework 1: Linear Classification and Subspaces

File Names-
1. NB_MNIST.ipynb - Naive Bayes on MNIST
2. NB_Wine.ipynb - Naive Bayes on Wine
3. PCA_LDA_NB.ipynb - PCA followed by LDA followed by Naive Bayes
4. PCA_LDA_NB_Wine.ipynb - PCA followed by LDA followed by Wine
5. PCA_NB_Wine.ipynb- PCA folllowed by Naive Bayes on Wine
6. PCA_NB_MNIST.ipynb - PCA followed by Naive Bayes on MNIST
7. train.csv - MNIST train
8. test.csv - MNIST testset
9. wine.data.txt - Wine Dataset

Homework 2: Random Forests

1.Random Forest -MNIST Dataset
2.Random Forest-Cover Dataset


Homework 3: K-Nearest Neighbour
1.K-Nearest Neighbour-MNIST
2.K-Nearest Neighbour-COVER Dataset