/Self-Organizing-Maps-using-KNN

High Frequency Time series Anomaly Detection using Self Organizing Maps (SOM) which is based on Competitive Learning a variant of the Neural Networks using K Nearest Neighbors

Primary LanguageJupyter Notebook

Time Series Anomaly Detection and Feature creation APIs

Self-Organizing-Maps-using-KNN

High Frequency Time series Anomaly Detection using Self Organizing Maps (SOM) which is based on Competitive Learning a variant of the Neural Networks using K Nearest Neighbor

Follow these steps

  • Download this folder, cd into the folder
  • then do "pip install -e ."
  • This will install the python files as a package in your local machine which will get updated even after you do some changes in the python files.
  • To see the main files go to anomaly detectors folder where all python files are placed.
  • In this specific folder is there for a specific detector, which has all important master python files
  • And all other dependencies are located in utils and reader_writer folder for main master python file
  • All the notebooks are placed in Notebook folder in parent folder along with datasets and setup file,etc. s