64 articles for “Ensemble Learning”

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Research ArticleOpen accessIn the abstractMeasuring the Relevance of Trajectory Matching and Profile Matching in the Context of Carpooling Computational SystemsMichael Cruz, Hendrik Macedo, Adolfo GuimarãesCarpooling consists of sharing individual vehicle space among people with comparable trajectories. Although there are some software initiatives to help carpooling practice, none of them really implements features similarly to searching for people with similar trajectories and profile. In this study, we propose an innovative approach to generate clusters of users that share similar trajectories and profile for carpooling purposes … …Journal of Computer Science, Vol. 14, Issue 2 · 3 Feb 2018 · 8,128 accessesView PDF Cite

InvestigationOpen accessIn the abstractA Conceptualization of Distributed Computation for Machine Learning: The Voting AlgorithmTalal Talib JameelThis paper describes a voting algorithm that can be used to find the most optimal solution to clustering problems in machine learning. As part of the family of algorithms known as Condorcet methods, the voting algorithm is used to choose a particular candidate, even in the absence of a definitive majority. The algorithm proceeds in two steps: Renormalization and reconciliation. … …American Journal of Engineering and Applied Sciences, Vol. 10, Issue 1 · 2 Mar 2017 · 7,890 accessesView PDF Cite

Research ArticleOpen accessIn the abstractSurvival and Change of Mahoree Tradition in Cambodian SocietyPittayawat Pantasri, Jarernchai Chonpairot, Boonsom YodmaleeProblem statement: Mahoree, is an important music ensemble in Cambodia since the Angkorean period. Mahoree formerly belonged to the court or noble Cambodian families. Mahoree is very popular and practiced by ordinary people and plays an important role in Cambodian society. Mahoree is a culture of the community and the Cambodian society and can be preserved and promoted by community … …Journal of Social Sciences, Vol. 8, Issue 2 · 13 Mar 2012 · 8,662 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBoosting Kernel Discriminative Common Vectors for Face RecognitionC. Lakshmi, M. PonnavaikkoProblem statement: Kernel discriminative common vector (KDCV) was one of the most effective non-linear techniques for feature extraction from high dimensional data including images and text data. Approach: This study presented a new algorithm called Boosting Kernel Discriminative Common Vector (BKDCV) to further improve the overall performance of KDCV by integrating the boosting and KDCV techniques. Results: In BKDCV, the … …Journal of Computer Science, Vol. 5, Issue 11 · 30 Nov 2009 · 6,571 accessesView PDF Cite