HighUtilityGeoreferencedFrequentPatternMining

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

Bases: PatternMiner

About this algorithm

Description:

This module implements the SHUFIM algorithm for mining high utility georeferenced frequent patterns from utility transactional datasets enriched with spatial information. It extends high utility pattern mining by integrating geospatial neighborhood data through a neighborhood file.

This approach is useful in spatial data mining applications where both utility and location influence pattern discovery, such as in retail location analysis or geographic resource optimization.

Parameters:

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

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

Attributes:

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

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

Execution methods

Calling from a Python program

from geoanalytics.patternMining import HighUtilityGeoreferencedFrequentPatternMining

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

miner.run(minSupport=3, minUtil=50, nFile="data/neighbor.txt")

Credits

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

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

Executes the SHUFIM algorithm to mine high utility georeferenced frequent patterns.

Parameters:

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

• minUtil (int) – Minimum utility threshold to identify high utility patterns.

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

Output:

Prints the discovered high utility georeferenced frequent patterns to the console.