9 citations · 16 across the 4 of their papers we have counts for
4 papers · 1 filter
Introducing Partial Matching Approach in Association Rules for Better Treatment of Missing Values
Shariq Bashir, Saad Razzaq, Umer Maqbool +2
Handling missing values in training datasets for constructing learning models or extracting useful information is considered to be an important research task in data mining and kno…
Using Association Rules for Better Treatment of Missing Values
Shariq Bashir, Saad Razzaq, Umer Maqbool +2
The quality of training data for knowledge discovery in databases (KDD) and data mining depends upon many factors, but handling missing values is considered to be a crucial factor…
Fast Algorithms for Mining Interesting Frequent Itemsets without Minimum Support
Shariq Bashir, Zahoor Jan, Abdul Rauf Baig
Real world datasets are sparse, dirty and contain hundreds of items. In such situations, discovering interesting rules (results) using traditional frequent itemset mining approach…
Ramp: Fast Frequent Itemset Mining with Efficient Bit-Vector Projection Technique
Shariq Bashir, Abdul Rauf Baig
Mining frequent itemset using bit-vector representation approach is very efficient for dense type datasets, but highly inefficient for sparse datasets due to lack of any efficient…