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Examples

In the repository link you can find multiple examples of how to use the library.

The few most prominent examples are:

  1. Concept-Agnostic Example - This example show how to create a simple dataset with 3 concepts and carry out a concept agnostic scenario with CumulativeStrategy and OneCLassSVM model. Leveraged data is randomly generated to show how to create a ConceptDataset using any numpy data.
  2. Concept-Incremental Example - This example show how to create a simple dataset with 4 concepts and carry out a concept incremental scenario with CumulativeStrategy and IsolationForest model. Leveraged data comes from different normal distributions to showcase forgetting and knowledge retention.
  3. Concept-Aware Example - This example showcase how to run a concept aware scenario using the NSL-KDD dataset stored in resources directory. The scenario includes IsolationForestAdapter model and Replay strategy.
  4. UNSW Dataset Example - This example showcase how to run a concept aware scenario using the UNSW dataset adopted to continual anomaly detection. The scenario includes VAE model and Replay strategy.
  5. Energy Dataset Example - This example showcase how to run a concept aware scenario using the Energy dataset adopted to continual anomaly detection. The scenario includes LocalOutlierFactor model and Cumulative strategy.
  6. Plot Heatmap Example - This example showcases how to generate a ROC-AUC heatmap for the results of a concept aware scenario
  7. Models examples - This directory contains multiple examples of how to use the models available in pyCLAD. Each example is a standalone script that demonstrates how to use a specific model with a specific strategy and dataset.