The goal of the project is to use principal component analysis to perform a classification task for which the training data is fewer than what is needed for a deep learning model. I worked on the Pima Indians Diabetes Data Set (https://www.kaggle.com/dssariya/pima-indians-diabetes-data-set) I successfully implemented the model and a comparison with a solution without PCA gave useful insights in understanding the results.
forked from amttar/PIMA-Dataset-Classification-using-PCA
-
Notifications
You must be signed in to change notification settings - Fork 0
The goal of the project is to use principal component analysis to perform a classification task for which the training data is fewer than what is needed for a deep learning model. I worked on the Pima Indians Diabetes Data Set (https://www.kaggle.com/dssariya/pima-indians-diabetes-data-set) I successfully implemented the model and a comparison w…
Srish2712/PIMA-Dataset-Classification-using-PCA
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
The goal of the project is to use principal component analysis to perform a classification task for which the training data is fewer than what is needed for a deep learning model. I worked on the Pima Indians Diabetes Data Set (https://www.kaggle.com/dssariya/pima-indians-diabetes-data-set) I successfully implemented the model and a comparison w…
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published
Languages
- Jupyter Notebook 100.0%