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Clustering is unsupervised learning where ideally class levels and number of clusters (K) are not known. K-clustering can be categorized as semi-supervised learning where K is known. Here we have considered K-Clustering with simultaneous feature selection. Feature subset selection helps to identify relevant features for clustering, increase(More)
Many different types of hyperkinetic and hypokinetic movement disorders have been reported after ischaemic and haemorrhagic stroke. We searched the Medline database from 1966 to February 2008, retrieving 2942 articles from which 156 relevant case reports, case series and review articles were identified. The papers were then further reviewed and filtered and(More)
The aim of the paper is to study a real coded multi objective genetic algorithm based K-clustering, where K represents the number of clusters, may be known or unknown. If the value of K is known, it is called K-clustering algorithm. The searching power of Genetic Algorithm (GA) is exploited to get for proper clusters and centers of clusters in the feature(More)
Classification rule mining is one of the important data mining tasks. Optimized Rule Set (ORS) generation is a major challenge. Multi Objective Genetic Algorithm (MOGA) has been used to search available data effectively and among many objectives instead of single objective with its real coded elitist version along with special operator. Some Data Sets (DSs)(More)
BACKGROUND AND PURPOSE There is limited information on outcomes from rapid access transient ischemic attack (TIA) clinics. We present 4-year outcomes of TIAs, strokes, and mimics from a UK TIA clinic database. METHODS All patients referred between April 2010 and May 2012 were retrospectively identified and outcomes determined. End points were stroke,(More)
BACKGROUND The Stroke 90 Project was implemented to reduce delays to stroke thrombolysis and involved 7 hospitals and 2 ambulance services in the Avon, Gloucester, Wiltshire and Somerset regional network. Interventions included a direct to CT (DtoCT) protocol for paramedics to transport patients directly to the CT scanner. Coincidentally, there were severe(More)
In the paper, real coded multi objective genetic algorithm (MOGA) based K-clustering method has been studied where K represents the number of clusters known a priori. Proposed method has the capability to deal with continuous and categorical features (mixed features) of data set. Commonly means and modes of features represents clusters for continuous and(More)