Skip to content

Frequent Pattern mining in tree-like sequences for medical data.

Notifications You must be signed in to change notification settings

geektoni/complex-frequent-sequence-mining

Repository files navigation

Sequential Pattern Mining with Complex Structure

Evaluation of an approximate approach on synthetic and medical data.

Main Programs:

The code needs Python 3.0 in order to be run.

  • main.py
    • It manages the three algorithms to assess the Sequential Pattern Mining problem.
    • It contains an helper that provide all the information to run the code.
  • generator/dataset_generator.py
    • It contains a simple code to generate a random dataset of sequences of complex structure.
    • There is the gen.sh to generate automatically a set of datasets throught this script

Supporting code

- print_graphs.py -> Support program to generate graphics on results
- comparator.py   -> Support program to compare .db outputs

Project Structure

The directory is structured as follow:

  • generator:
    • It contains the script used to generate the synthetic datasets.
  • datasets:
    • It contains the input datasets, generated or not by the dataset_generator
    • if generated, the name contains the information about the setting used
  • experiments:
    • It contains the csv output data of the main program
    • Each row contains specific information about a single algorithm execution
  • results:
    • It contains the .db output data of the main program
    • Each file contains the frequent sequences the main program found
    • The name define the algorithm used and information to recover the input data
  • data_printers:
    • It contains some helper scripts used to generate the graphs.

Synthetic Medical Dataset

https://synthetichealth.github.io/synthea/

About

Frequent Pattern mining in tree-like sequences for medical data.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published