6 citations · 12 across the 7 of their papers we have counts for
5 papers · 1 filter
Adaptive Decision Forest: An Incremental Machine Learning Framework
Md Geaur Rahman, Md Zahidul Islam
In this study, we present an incremental machine learning framework called Adaptive Decision Forest (ADF), which produces a decision forest to classify new records. Based on our tw…
FastForest: Increasing Random Forest Processing Speed While Maintaining Accuracy
Darren Yates, Md Zahidul Islam
Random Forest remains one of Data Mining's most enduring ensemble algorithms, achieving well-documented levels of accuracy and processing speed, as well as regularly appearing in n…
A Novel Incremental Clustering Technique with Concept Drift Detection
Mitchell D. Woodbright, Md Anisur Rahman, Md Zahidul Islam
Data are being collected from various aspects of life. These data can often arrive in chunks/batches. Traditional static clustering algorithms are not suitable for dynamic datasets…
Tree Index: A New Cluster Evaluation Technique
A. H. Beg, Md Zahidul Islam, Vladimir Estivill-Castro
We introduce a cluster evaluation technique called Tree Index. Our Tree Index algorithm aims at describing the structural information of the clustering rather than the quantitative…
DataLearner: A Data Mining and Knowledge Discovery Tool for Android Smartphones and Tablets
Darren Yates, Md Zahidul Islam, Junbin Gao
Smartphones have become the ultimate 'personal' computer, yet despite this, general-purpose data-mining and knowledge discovery tools for mobile devices are surprisingly rare. Data…