Monzurur Rahman

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—Missing value imputation is one of the biggest tasks of data pre-processing when performing data mining. Most medical datasets are usually incomplete. Simply removing the cases from the original datasets can bring more problems than solutions. A suitable method for missing value imputation can help to produce good quality datasets for better analysing(More)
—Most medical datasets are not balanced in their class labels. Indeed in some cases it has been no ticed that the given class labels do not accurately represent characteristics of the data record. Most existing classification methods tend not to perform well on minority class examples when the dataset is extremely imbalanced. This is because they aim to(More)
Missing value imputation is one of the biggest tasks of data pre-processing when performing data mining. Most medical datasets are usually incomplete. Simply removing the cases from the original datasets can bring more problems than solutions. A suitable method for missing value imputation can help to produce good quality datasets for better analysing(More)
The multiprocessor task graph scheduling problem has been extensively studied as academic optimization problem which occurs in optimizing the execution time of parallel algorithm with parallel computer. The problem is already being known as one of the NP-hard problems. There are many good approaches made with many optimizing algorithm to find out the(More)