LocalPeriodicPatternMining

class geoanalytics.patternMining.LocalPeriodicPatternMining.LocalPeriodicPatternMining(inputFile: str)[source]

Bases: PatternMiner

About this algorithm

Description:

This module implements the LPPGrowth algorithm for mining local periodic patterns from temporal transactional datasets. The algorithm identifies patterns with periodic recurrence within local temporal windows, controlled by maximum periodicity, maximum sub-periodicity, and minimum duration thresholds.

Parameters:

  • inputFile (str): Path to the temporal transactional database file.

Attributes:

  • inputFile (str): The temporal transactional input file provided during object instantiation.

  • miner (LPPGrowth): Instance of the LPPGrowth algorithm from the PAMI library.

Execution methods

Calling from a Python program

from geoanalytics.patternMining import LocalPeriodicPatternMining

miner = LocalPeriodicPatternMining("data/input.txt")

miner.run(maxPer=10, maxSoPer=5, minDur=3)

Credits

Written by M. Charan Teja, under the guidance of Professor Rage Uday Kiran.

run(maxPer: int, maxSoPer: int, minDur: int)[source]

Executes the LPPGrowth algorithm to mine local periodic patterns.

Parameters:

  • maxPer (int) – Maximum periodicity threshold controlling pattern recurrence interval.

  • maxSoPer (int) – Maximum sub-periodicity threshold controlling pattern sub-intervals.

  • minDur (int) – Minimum duration threshold specifying the minimal length of the periodic pattern.

Output:

Prints the discovered local periodic patterns to the console.