4 results for “cluster validation”

Set a search alert

Research ArticleOpen accessIn the keywordsA Density Based Dynamic Data Clustering Algorithm based on Incremental DatasetS. Angel Latha Mary, K.R. Shankar KumarProblem statement: Clustering and visualizing high-dimensional dynamic data is a challenging problem. Most of the existing clustering algorithms are based on the static statistical relationship among data. Dynamic clustering is a mechanism to adopt and discover clusters in real time environments. There are many applications such as incremental data mining in data warehousing applications, sensor network, which relies on dynamic … …Journal of Computer Science, Vol. 8, Issue 5 · 20 Feb 2012 · 7,469 accessesView PDF Cite

Review ArticleOpen accessIn the abstractEconomic Theory and Machine Learning Integration in Asset Pricing and Portfolio Optimization: A Bibliometric Analysis and Conceptual FrameworkPatrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik FaturohmanThe integration of Machine Learning (ML) with economic theory has transformed financial market analysis, particularly in asset pricing and portfolio optimization. This study synthesizes existing research, identifies gaps and elucidates ML's impact on enhancing economic models and strategies through a Systematic Literature Review (SLR) of 401 relevant documents using bibliometric methodology and VOS viewer. Results show an increasing trend in … …Journal of Computer Science, Vol. 20, Issue 10 · 7 Aug 2024 · 5,725 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCOMBINATION OF DIFFERENCE SUBSPACE AND OPPURTUNISTIC CLUSTERING ON HIGH DIMENSIONAL DATAM. Ravichandran, A. ShanmugamClustering is recognized as sigificant technique for analysing data and concentric effort has been taken in different domains comprises of recognition of pattern, statistical analysis and data mining for decades. Subspace clustering is developed from the group of cluster objects from all subspaces of a dataset. During clustering of objects involing higher dimension, the accuracy and effectiveness of traditional clustering … …Journal of Computer Science, Vol. 10, Issue 8 · 11 Mar 2014 · 6,359 accessesView PDF Cite

Research ArticleOpen accessIn the abstractFuzzy Modeled K-Cluster Quality Mining of Hidden Knowledge for Decision SupportS. Parkash Kumar, K. S. RamaswamiProblem statement: The work presented Fuzzy Modeled K-means Cluster Quality Mining of hidden knowledge for Decision Support. Based on the number of clusters, number of objects in each cluster and its cohesiveness, precision and recall values, the cluster quality metrics is measured. The fuzzy k-means is adapted approach by using heuristic method which iterates the cluster to form an efficient … …Journal of Computer Science, Vol. 7, Issue 11 · 24 Aug 2011 · 6,677 accessesView PDF Cite