PartialPeriodicPatternInMultipleTimeSeries

class geoanalytics.patternMining.PartialPeriodicPatternInMultipleTimeSeries.PartialPeriodicPatternInMultipleTimeSeries(inputFile: str)

Bases: PatternMiner

About this algorithm

Description:

This module implements the PPGrowth algorithm for mining partial periodic patterns across multiple temporal transactional datasets (multiple time series). It identifies itemsets exhibiting periodic behavior with respect to a specified period and minimum periodic support threshold across multiple series.

Parameters:

• inputFile (str): Path to the temporal transactional database file containing multiple time series.

Attributes:

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

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

Execution methods

Calling from a Python program

from geoanalytics.patternMining import PartialPeriodicPatternInMultipleTimeSeries

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

miner.run(period=12, periodicSupport=5)

Credits

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

run(period: int, periodicSupport: int)

Executes the PPGrowth algorithm to mine partial periodic patterns in multiple time series.

Parameters:

• period (int) – The periodicity window to evaluate pattern repetition.

• periodicSupport (int) – Minimum periodic support threshold indicating required occurrences within the period.

Output:

Prints the discovered partial periodic patterns across multiple time series to the console.