GitHub - AnjumeeJeba/Autoencoder-6G-subTHz: We utilized an autoencoder-based anomaly detection technique to compress the dataset into a latent space with a reduced dimension (32-dimensional) compared to the original data (1500-dimensional).

AnjumeeJeba / Autoencoder-6G-subTHz Public

Notifications You must be signed in to change notification settings
Fork 0
Star 1

We utilized an autoencoder-based anomaly detection technique to compress the dataset into a latent space with a reduced dimension (32-dimensional) compared to the original data (1500-dimensional).

1 star 0 forks Branches Tags Activity

Star

Notifications

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
AutoEncoderModel(80%-20%).ipynb		AutoEncoderModel(80%-20%).ipynb
shuffled_allfinalcopy6.csv		shuffled_allfinalcopy6.csv

About

We utilized an autoencoder-based anomaly detection technique to compress the dataset into a latent space with a reduced dimension (32-dimensional) compared to the original data (1500-dimensional).

Activity

1 star

1 watching

0 forks

Report repository