Skip to content

A semi-supervised density-based learning framework for non-stationary environments

Notifications You must be signed in to change notification settings

bruno-accioli/AMANDA

 
 

Repository files navigation

#AMANDA: Semi-supervised approach for learning on environments with gradual drift and extreme verification latency

You can test the framework for artificial datasets through a jupyter notebook in Datasets/benchmarking/sinthetic/BATCH_MODE

You can test the framework for real datasets through a jupyter notebook in Datasets/benchmarking/real/BATCH_MODE

**We are refining and cleaning the code. It is not a final version.

About

A semi-supervised density-based learning framework for non-stationary environments

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Gnuplot 85.3%
  • Jupyter Notebook 14.7%