StablePeriodicPatternMining

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

Bases: PatternMiner

About this algorithm

Description:

This module implements the SPPGrowth algorithm for mining stable periodic frequent patterns from temporal databases. It discovers itemsets that appear frequently with stable periodicity under given constraints on maximum period and maximum latency.

Parameters:

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

Attributes:

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

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

Execution methods

Calling from a Python program

from geoanalytics.patternMining import StablePeriodicPatternMining

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

miner.run(minSupport=3, maxPer=10, maxLa=5)

Credits

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

run(minSupport: int, maxPer: int, maxLa: int)[source]

Runs the SPPGrowth algorithm to mine stable periodic patterns.

Parameters:

  • minSupport (int) – Minimum support threshold for patterns.

  • maxPer (int) – Maximum period allowed for the patterns.

  • maxLa (int) – Maximum latency allowed for the patterns.

Output:

Prints the discovered stable periodic patterns to the console.