PAMI.highUtilityFrequentPattern.basic package

Submodules

PAMI.highUtilityFrequentPattern.basic.HUFIM module

class PAMI.highUtilityFrequentPattern.basic.HUFIM.HUFIM(iFile: str, minUtil: int | float, minSup: int | float, sep: str = '\t')[source]

Bases: _utilityPatterns

Description:

HUFIM (High Utility Frequent Itemset Miner) algorithm helps us to mine High Utility Frequent ItemSets (HUFIs) from transactional databases.

Reference:

Kiran, R.U., Reddy, T.Y., Fournier-Viger, P., Toyoda, M., Reddy, P.K., & Kitsuregawa, M. (2019). Efficiently Finding High Utility-Frequent Itemsets Using Cutoff and Suffix Utility. PAKDD 2019. DOI: 10.1007/978-3-030-16145-3_15

Parameters:

iFile – str : Name of the Input file to mine complete set of Geo-referenced frequent sequence patterns
oFile – str : Name of the output file to store complete set of Geo-referenced frequent sequence patterns
minSup – int or float or str : The user can specify minSup either in count or proportion of database size. If the program detects the data type of minSup is integer, then it treats minSup is expressed in count. Otherwise, it will be treated as float.
minUtil – int : The user given minUtil value.
candidateCount – int Number of candidates
maxMemory – int Maximum memory used by this program for running
nFile – str : Name of the input file to mine complete set of Geo-referenced frequent sequence patterns
sep – str : This variable is used to distinguish items from one another in a transaction. The default seperator is tab space. However, the users can override their default separator.

Attributes:

iFilefile: Name of the input file to mine complete set of patterns
oFilefile: Name of the output file to store complete set of patterns
memoryRSSfloat: To store the total amount of RSS memory consumed by the program
startTime:float: To record the start time of the mining process
endTime:float: To record the completion time of the mining process
minUtilint: The user given minUtil value
minSupfloat: The user given minSup value
highUtilityFrequentItemSets: map: set of high utility frequent itemSets
candidateCount: int: Number of candidates
utilityBinArrayLU: list: A map to hold the local utility values of the items in database
utilityBinArraySU: list: A map to hold the subtree utility values of the items is database
oldNamesToNewNames: list: A map which contains old names, new names of items as key value pairs
newNamesToOldNames: list: A map which contains new names, old names of items as key value pairs
singleItemSetsSupport: map: A map which maps from single itemsets (items) to their support
singleItemSetsUtility: map: A map which maps from single itemsets (items) to their utilities
maxMemory: float: Maximum memory used by this program for running
patternCount: int: Number of RHUI’s
itemsToKeep: list: keep only the promising items i.e items that can extend other items to form RHUIs
itemsToExplore: list: list of items that needs to be explored

Methods:

mine(): Mining process will start from here
getPatterns(): Complete set of patterns will be retrieved with this function
save(oFile): Complete set of patterns will be loaded in to a output file
getPatternsAsDataFrame(): Complete set of patterns will be loaded in to a dataframe
getMemoryUSS(): Total amount of USS memory consumed by the mining process will be retrieved from this function
getMemoryRSS(): Total amount of RSS memory consumed by the mining process will be retrieved from this function
getRuntime(): Total amount of runtime taken by the mining process will be retrieved from this function
backTrackingHUFIM(transactionsOfP, itemsToKeep, itemsToExplore, prefixLength): A method to mine the RHUIs Recursively
useUtilityBinArraysToCalculateUpperBounds(transactionsPe, j, itemsToKeep): A method to calculate the sub-tree utility and local utility of all items that can extend itemSet P and e
output(tempPosition, utility): A method to output a relative-high-utility itemSet to file or memory depending on what the user chose
isEqual(transaction1, transaction2): A method to Check if two transaction are identical
useUtilityBinArrayToCalculateSubtreeUtilityFirstTime(dataset): A method to calculate the sub tree utility values for single items
sortDatabase(self, transactions): A Method to sort transaction
sortTransaction(self, trans1, trans2): A Method to sort transaction
useUtilityBinArrayToCalculateLocalUtilityFirstTime(self, dataset): A method to calculate local utility values for single itemSets

Executing the code on terminal

Format:

(.venv) $ python3 HUFIM.py <inputFile> <outputFile> <minUtil> <sep>

Example Usage:

(.venv) $ python3 HUFIM.py sampleTDB.txt output.txt 35 20

(.venv) $ python3 HUFIM.py sampleTDB.txt output.txt 35 20

Note

minSup will be considered in percentage of database transactions

Sample run of importing the code

from PAMI.highUtilityFrequentPattern.basic import HUFIM as alg

obj=alg.HUFIM("input.txt", 35, 20)

obj.mine()

Patterns = obj.getPatterns()

print("Total number of high utility frequent Patterns:", len(Patterns))

obj.save("output")

memUSS = obj.getMemoryUSS()

print("Total Memory in USS:", memUSS)

memRSS = obj.getMemoryRSS()

print("Total Memory in RSS", memRSS)

run = obj.getRuntime()

print("Total ExecutionTime in seconds:", run)

Credits:

The complete program was written by pradeep pallikila under the supervision of Professor Rage Uday Kiran.

getMemoryRSS() → float[source]: Total amount of RSS memory consumed by the mining process will be retrieved from this function :return: returning RSS memory consumed by the mining process :rtype: float

getMemoryUSS() → float[source]: Total amount of USS memory consumed by the mining process will be retrieved from this function :return: returning USS memory consumed by the mining process :rtype: float

getPatterns() → Dict[str, List[int | float]][source]: Function to send the set of patterns after completion of the mining process :return: returning patterns :rtype: dict

getPatternsAsDataFrame() → DataFrame[source]: Storing final patterns in a dataframe :return: returning patterns in a dataframe :rtype: pd.DataFrame

getRuntime() → float[source]: Calculating the total amount of runtime taken by the mining process :return: returning total amount of runtime taken by the mining process :rtype: float

mine() → None[source]: High Utility Frequent Pattern mining start here :return: None

printResults() → None[source]: This function is used to print the results

save(outFile: str) → None[source]: Complete set of frequent patterns will be loaded in to an output file :param outFile: name of the output file :type outFile: csv file :return: None

startMine() → None[source]: High Utility Frequent Pattern mining start here :return: None