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Unsupervised learning for historical data validation (Udava).

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UDAVA

Unsupervised learning for DAta VAlidation.

Installation

Developed using Python3.8. You can install the required modules by creating a virtual environment and install the requirements.txt-file (run these commands from the main folder):

mkdir venv
python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt

Udava as a Service

Start the server by running:

python3 src/api.py

Parameters

  • featurize
    • dataset
    • window_size
    • overlap
    • timestamp_column
    • columns
  • cluster
    • learning_method
    • n_clusters
    • max_iter
    • use_predefined_centroids
    • fix_predefined_centroids
    • annotations_dir
    • min_segment_length: A segment is defined as a section of the time series that has an uninterrupted sequence of data points with the same cluster label. This parameter defines the minimum length such a sequence should have. If a segment is shorter than this length, the data points will be reassigned to another cluster.
  • evaluate

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Unsupervised learning for historical data validation (Udava).

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