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47 articles for “dimensionality”
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Research ArticleOpen accessIn the abstractFeature Selection for High Dimensional Data: An Evolutionary Filter ApproachAnwar Ali Yahya, Addin Osman, Abd Rahman Ramli, Adlan BalolaProblem statement: Feature selection is a task of crucial importance for the application of machine learning in various domains. In addition, the recent increase of data dimensionality poses a severe challenge to many existing feature selection approaches with respect to efficiency and effectiveness. As an example, genetic algorithm is an effective search algorithm that lends itself directly to feature selection; … …Journal of Computer Science, Vol. 7, Issue 5 · 9 May 2011 · 7,949 accessesView PDFCite
Research ArticleOpen accessIn the abstractIndex Financial Time Series Based on Zigzag-Perceptually Important PointsAli Selamat, Chawalsak Phetchanchai, Tanzila Saba, Amjad RehmanProblem statement: Financial time series were usually large in size, unstructured and of high dimensionality. Since, the illustration of financial time series shape was typically characterized by a few number of important points. These important points moved in zigzag directions which could form technical patterns. However, these important points exhibited in different resolutions and difficult to determine. Approach: In this … …Journal of Computer Science, Vol. 6, Issue 12 · 2 Nov 2010 · 9,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Threshold Based Compressive Sensing Algorithm in Wireless Sensor NetworkParnasree Chakraborty, C. ThariniWireless Sensor Networks (WSN) are comprised of spatially distributed sensor nodes, where each node contains sensors, processors and transceivers for communicating data. Regardless of the application in which the sensor network is serving, the data generated in the network eventually must be delivered to the sink. However the limited network bandwidth, frequent node/link failure along with the unreliable communication medium … …American Journal of Applied Sciences, Vol. 14, Issue 2 · 3 Feb 2017 · 7,512 accessesView PDFCite
EditorialOpen accessIn the abstractBig Data and Parkinson’s Disease - from Understanding of Disease to Personalised MedicineYen F. Tai, Nicola PaveseThe advancement of information technology in recent years has generated a huge amount of datasets in all areas of scientific research. This has led to new opportunities to harness the 'Big Data' to improve our understanding of diseases - from investigating disease mechanisms to monitoring treatment responses. The Big Data approach is a data-driven and often hypothesis-free, way of studying … …Neuroscience International, Vol. 7, Issue 1 · 27 Jul 2016 · 7,761 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Breast Tumor in Mammogram Images Using Unsupervised Feature LearningAidarus M. Ibrahim, Baharum Baharudin, Abas Md Said, P. N. HashimahIn this study, we propose a learning-based approach using feature learning to minimize the manual effort required to extract features. Firstly, we extracted features from equally spaced sub-patches covering the input Region of Interest (ROI). The dimensionality of the extracted features is reduced using max-pooling. Furthermore, spherical k-means clustering coupled with max pooling (k-means-max pooling) is compared with well-known feature … …American Journal of Applied Sciences, Vol. 13, Issue 5 · 13 May 2016 · 7,503 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Distinguishability Based Weighted Feature Selection Algorithms for Improved Classification of Gene Microarray DatasetJ. Jeyachidra, M. PunithavalliData mining played vital role in comprehending, analyzing, understanding and interpreting microarray technology expression data. That includes search for genes that had similar or correlated patterns of expression. For that, the feature selection was one of the frequently used important techniques for data preprocessing. Many feature selection algorithms had been developed. Yet the persisting problem was in selecting optimal subset … …Journal of Computer Science, Vol. 11, Issue 2 · 2 Feb 2015 · 6,380 accessesView PDFCite
Research ArticleOpen accessIn the abstractRADIUS BASED BLOCK LOCAL BINARY PATTERN ON T-ZONE FACE AREA FOR FACE RECOGNITIONMd. Jan Nordin, Abdul Aziz K. Abdul Hamid, Sumazly Ulaiman, R. U. GobithaasanThis study presents a comparison of recognition performance between feature extraction on the T-Zone face area and Radius based block on the critical point. A T-Zone face image is first divided into small regions where Local Binary Pattern (LBP) histograms are extracted and then concatenated into a single feature vector. This feature vector will further reduce the dimensionality scope by … …Journal of Computer Science, Vol. 10, Issue 12 · 27 Dec 2014 · 7,971 accessesView PDFCite
Research ArticleOpen accessIn the abstractA COMPARATIVE STUDY OF COMBINED FEATURE SELECTION METHODS FOR ARABIC TEXT CLASSIFICATIONAisha Adel, Nazlia Omar, Adel Al-ShabiText classification is a very important task due to the huge amount of electronic documents. One of the problems of text classification is the high dimensionality of feature space. Researchers proposed many algorithms to select related features from text. These algorithms have been studied extensively for English text, while studies for Arabic are still limited. This study introduces an investigation … …Journal of Computer Science, Vol. 10, Issue 11 · 20 Dec 2014 · 8,439 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Classification Algorithms on Medical Diagnoses-a SurveyS. Vanaja, K. RameshkumarThe aim of this research paper is to study and discuss the various classification algorithms applied on different kinds of medical datasets and compares its performance. The classification algorithms with maximum accuracies on various kinds of medical datasets are taken for performance analysis. The result of the performance analysis shows the most frequently used algorithms on particular medical dataset and … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Sep 2014 · 7,364 accessesView PDFCite
Research ArticleOpen accessIn the abstractBRAIN TUMOR CLASSIFICATION BASED ON CLUSTERED DISCRETE COSINE TRANSFORM IN COMPRESSED DOMAINV. Anitha, S. MurugavalliThis study presents a novel method to classify the brain tumors by means of efficient and integrated methods so as to increase the classification accuracy. In conventional systems, the problem being the same to extract the feature sets from the database and classify tumors based on the features sets. The main idea in plethora of earlier researches related to any … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,537 accessesView PDFCite