Machine_learning-project

applications of different methods on dry_bean data set and some innovations

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
DryBeanDataset		DryBeanDataset
processed_data		processed_data
Clustered_Beans.xlsx		Clustered_Beans.xlsx
Dry_Bean_Dataset.arff		Dry_Bean_Dataset.arff
Dry_Bean_Dataset.csv		Dry_Bean_Dataset.csv
Dry_Bean_Dataset.txt		Dry_Bean_Dataset.txt
Dry_Bean_Dataset.xlsx		Dry_Bean_Dataset.xlsx
LICENSE		LICENSE
README.md		README.md
RF.py		RF.py
SVM.py		SVM.py
bagging.py		bagging.py
checkpoint.npz		checkpoint.npz
decisiontree.py		decisiontree.py
grad_boo.ipynb		grad_boo.ipynb
interactive_3d_tsne.html		interactive_3d_tsne.html
log_regr.ipynb		log_regr.ipynb
logistic_regression_try.ipynb		logistic_regression_try.ipynb
new.ipynb		new.ipynb
preprocess_visualize.ipynb		preprocess_visualize.ipynb
resnet.ipynb		resnet.ipynb
testing_kmean.py		testing_kmean.py
timeline.docx		timeline.docx
tsne_visualization.png		tsne_visualization.png
xgboost.ipynb		xgboost.ipynb

Provide feedback