Calculate missing value using association rules mining

Anil Rajput, Manmohan Singh, Pooja Shrivastava

DOI: http://dx.doi.org/10.5138/bjdmn.v1i2.1242

Abstract


Discovering hidden knowledge from hug amount of data in form of association rules mining havebecome very popular in scaling field of data mining. One several algorithms have been alsodeveloped for mining association rules. All those algorithms can be effectively applied on all asdataset where data has not any time granularity means non-temporal dataset. The quality of trainingdata for knowledge discovery in databases (KDD) and data mining depends upon so many factors,but also handling missing values is considered to be a crucial factor in whole data quality. Today inreal world datasets contains missing values due to human, in operational error, hardwaremalfunctioning and many other factors.

Keywords


Data Mining, Temporal Frequent Pattern and Missing Value Quality of training data, association rules mining,

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