The class imbalance problem occurs when one far outnumbers the other classes, causing most traditional classifiers perform poorly on minority classes. To tackle this problem, a plethora of techniques have been proposed, especially centered around resampling methods. This paper introduces two-stage method that combines DBSCAN clustering algorithm to filter noisy majority instances with graph-bas...

This paper proposes a sampling based planning algorithm to control autonomous vehicles. We propose an improved Rapidly-exploring Random Tree which includes the definition of Knearest points and propose a two-stage sampling strategy to adjust RRT in other to perform maneuver while avoiding collision. The simulation results show the success of the algorithm.

The objective of this paper is to derived difference, regression and predictive estimators for two stage sampling by using double sampling technique when multi-auxiliary information is unavailable. The mean square errors for these estimators have been derived. A numerical study is given for finding the relative comparison.