Time Series Experiments Based on SAX Representation

This is an implementation of experiments from the paper that introduces the SAX (Symbolic Aggregate approXimation) representation of time series. You can read the paper here: SAX Paper.

Running Experiments

Hierarchical Clustering:

To run the Hierarchical Clustering experiment, use the following command:

python clustering.py --HC

Partitionary Clustering:

To run the Partitionary Clustering experiment, use the following command:

python clustering.py --PC

Nearest Neighbor Classification:

To run the Nearest Neighbor Classification experiment, use the following command:

python classification.py --NNC

Decision Tree Classification:

To run the Decision Tree Classification experiment, use the following command:

python classification.py --DTC

Anomaly Detection:

To run the Anomaly Detection experiment, use the following command:

python anomaly_detection.py --DTC