PAMI.extras.calculateMISValues package

Submodules

PAMI.extras.calculateMISValues.usingBeta module

class PAMI.extras.calculateMISValues.usingBeta.usingBeta(iFile: str, beta: int, threshold: int, sep: str)[source]

Bases: object

Description:

This code is used to calculate multiple minimum support of items in the the given database. Output can be stored in file or as as dataframe.

Parameters:

  • iFile – str : Name of the Input file to get the patterns as DataFrame

  • beta – str : Name of the output file to store complete set of frequent patterns

  • threshold – int : The user can specify threshold either in count or proportion of database size. If the program detects the data type of threshold is integer, then it treats threshold is expressed in count.

  • 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.

Importing this algorithm into a python program

from PAMI.extras.calculateMISValues import usingBeta as db

obj = db.usingBeta(iFile, 3, 16, “ “)

obj.save(oFile)

calculateMIS() → None[source]
getMISDataFrame() → DataFrame[source]

Storing items and its respective minimum support in a dataframe :return: returning items and its respective minimum support in a dataframe :rtype: pd.DataFrame

save(outFile: str) → None[source]

Complete set of items and its respective minimum support values will be loaded in to an output file :param outFile: name of the output file :type outFile: csv file :return: None

PAMI.extras.calculateMISValues.usingSD module

class PAMI.extras.calculateMISValues.usingSD.usingSD(iFile: str, threshold: int, sep: str)[source]

Bases: object

Description:

This code is used to calculate multiple minimum support of items in the the given database. Output can be stored in file or as as dataframe.

Parameters:

  • iFile – str : Name of the Input file to mine complete set of frequent patterns

  • sd – int : SD of items to mine complete set of frequent patterns.

  • threshold – int : The user can specify threshold either in count or proportion of database size. If the program detects the data type of threshold is integer, then it treats threshold is expressed in count.

  • 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.

Importing this algorithm into a python program

from PAMI.extras.calculateMISValues import usingSD as db

obj = db.usingSD(iFile, 16, "       ")

obj.getPatterns("outputFileName") # To create patterns in dataframe

obj.save(oFile)
calculateMIS() → None[source]
getDataFrame() → DataFrame[source]

Storing Items and its respective calculated minimum support values in a dataframe :return: returning Items and its respective calculated minimum support values in a dataframe :rtype: pd.DataFrame

save(outFile: str) → None[source]

Complete Items and its respective calculated minimum support values will be loaded in to an output file :param outFile: name of the output file :type outFile: csv file :return: None

Module contents