SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering
Classification datasets often have an unequal class distribution among their examples. This
problem is known as imbalanced classification. The Synthetic Minority Over-sampling …
problem is known as imbalanced classification. The Synthetic Minority Over-sampling …
[图书][B] Handbook of research on swarm intelligence in engineering
S Bhattacharyya - 2015 - books.google.com
Swarm Intelligence has recently emerged as a next-generation methodology belonging to
the class of evolutionary computing. As a result, scientists have been able to explain and …
the class of evolutionary computing. As a result, scientists have been able to explain and …
Learning imbalanced classifiers locally and globally with one-side probability machine
We consider the imbalanced learning problem, where the data associated with one class
are far fewer than those associated with the other class. Current imbalanced learning …
are far fewer than those associated with the other class. Current imbalanced learning …
APN model construction for malicious email detection
Abstract Recently, associative Petri nets (APNs) have been attracted in knowledge
representation and modeling of expert systems. However, it is a challenge in transferring …
representation and modeling of expert systems. However, it is a challenge in transferring …
Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data
Liquefaction in soil is one of the other major problems in geotechnical earthquake
engineering. This chapter adopts Minimax Probability Machine (MPM) for prediction of …
engineering. This chapter adopts Minimax Probability Machine (MPM) for prediction of …