GeoreferencedPeriodicFrequentPatternMining

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

Bases: PatternMiner

About this algorithm

Description:

This module implements the GPFPMiner algorithm for mining georeferenced periodic frequent patterns from temporal transactional datasets. The algorithm discovers itemsets that appear periodically over time, considering spatial relationships defined in a neighborhood file.

This method is useful in spatiotemporal data mining applications such as urban activity analysis, environmental monitoring, and other domains requiring periodic pattern discovery with spatial context.

Parameters:

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

• nFile (str): Path to the neighborhood file specifying spatial relationships.

Attributes:

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

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

Execution methods

Calling from a Python program

from geoanalytics.patternMining import GeoreferencedPeriodicFrequentPatternMining

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

miner.run(minSupport=3, maxPer=7, nFile="data/neighbor.txt")

Credits

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

run(minSupport: int, maxPer: int, nFile: str)

Executes the GPFPMiner algorithm to mine georeferenced periodic frequent patterns.

Parameters:

• minSupport (int) – Minimum support threshold for frequent itemsets.

• maxPer (int) – Maximum periodicity value defining pattern recurrence period.

• nFile (str) – Path to the neighborhood file containing spatial proximity information.

Output:

Prints the discovered georeferenced periodic frequent patterns to the console.