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Phyu TN (2009). You can download the paper by clicking the button above. /Type /Annot In: Daniilidis K, Maragos P, and Paragios N (Eds. Deng J, Berg AC, Li K, and Fei-Fei L (2010). endobj <>>> Bhatia N (2010). endobj 6tSqPXA ?ELl*@u/ntK"j `j"]w9,|97'|{%Pq/n?>!Bc?lcanu!ny{u8LGPswm;urfJa=/U qQRtG2pw*htH;lww}`97D"= LxY"JvB]=+EKjtrhcN Machine Learning, 20(3): 197-243. endobj 0000041295 00000 n << /C [0 1 1] /S /GoTo /H /I 387 88
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10 0 obj 0000115211 00000 n Han J, Kamber M, and Pei J (2011). endobj 0000003835 00000 n Keywords:Classification, Machine learning, Supervised learning, Classifiers, Article History:Received 5 May 2020, Received in revised form 20 August 2020, Accepted 10 September 2020. /Border [0 0 0]
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Power utility nontechnical loss analysis with extreme learning machine method. /Subtype /Link >> Neelamegam S and Ramaraj E (2013). IBM Journal of Research and Development, 44(1.2): 206-226. /Fm3 29 0 R CLASSIFIER SELECTION MODELS FOR INTRUSION DETECTION SYSTEM (IDS, Informatics Engineering, an International Journal (IEIJ), PRIVACY PRESERVATION TECHNIQUES IN DATA MINING, Supervised Machine Learning: A Review of Classification Techniques, Machine learning: a review of classification and combining techniques, An Effectual and Secure Approach for the Detection and Efficient Searching of Network Intrusion Detection System (NIDS), Comparison of Machine Learning Classifiers for Recognition of Online and Offline Handwritten Digits*, A SURVEY OF TEXT CLASSIFICATION ALGORITHMS, Fast Boost Decision Tree Algorithm: A novel classifier for the assessment of student performance in Educational data, Study on Classification of Plant Images using Combined Classifier, A Critical Study of Selected Classification Algorithms for Liver Disease Diagnosis, International Journal of Database Management Systems ( IJDMS ), Learning from Multiple Classifier Systems: Perspectives for Improving Decision Making of QSAR Models in Medicinal Chemistry, Journal of Computer Science IJCSIS July 2017 Part I.pdf, On Constructing a Financial Decision Support System, CLASSIFICATION ALGORITHM USING RANDOM CONCEPT ON A VERY LARGE DATA SET: A SURVEY, A new feature weighted fuzzy clustering algorithm, A DETAILED STUDY ON CLASSIFICATION TECHNIQUES FOR DATA MINING, BREAST CANCER DIAGNOSIS VIA DATA MINING: PERFORMANCE ANALYSIS OF SEVEN DIFFERENT ALGORITHMS, Computer Science & Engineering: An International Journal (CSEIJ), AN APPROACH TO VARIABLE SELECTION IN EFFICIENCY ANALYSIS, Assessing Supervised Machine Learning Techniques for Predicting Student Learning Preferences, Classification Techniques in Machine Learning: Applications and Issues, Efficient Intrusion Classification in Network Using Supervised Data Miningtechniques, A Comparative Study of Data Mining approaches for Bag of Visual Words Based Image Classification, Comparative Study of Four Supervised Machine Learning Techniques for Classification, Data ClassifiCation Algorithms and Applications, APPROACHES FOR EFFICIENT HANDLING OF LARGE DATASETS, OUT-OF-CORE DATA HANDLING WITH PERIODIC PARTIAL RESULT MERGING, A Survey Paper on Classification Algorithms in Big Data, Improved Algorithm for Network Intrusion Detection System based on K-Nearest Neighbour: Survey, IJIRST - International Journal for Innovative Research in Science and Technology, A REVIEW ON TECHNIQUES FOR CLASSIFICATION OF TWITTER DATA USING BIG DATA, Data Mining Methods for Recommender Systems, Categorization of large text collections: Feature selection for training neural networks, I S S N : 1 6 9 4 -2 5 0 7 ( P r i n t ) I S S N : 1 6 9 4 -2 1 0 8 ( O n l i n e, Designing A Method for Alcohol Consumption Prediction Based on Clustering and Support Vector Machines, Terrorist Group Prediction Using Data Classification, Scaling up Detection Rates and Reducing False Positives in Intrusion Detection using NBTree, Intelligent Systems Reference Library 72 Data Preprocessing in Data Mining, Comparison of Classification Models for Early 0000115748 00000 n /C [0 1 0] >> /Rect [144.778 181.873 203.985 193.444] /Border [0 0 0] /S /URI << 0000008925 00000 n endobj >> /A Yang Y and Webb GI (2009). << << Springer Nature, Berlin, Germany. 0000115295 00000 n 0000014275 00000 n /D [null /XYZ 89.291 390.953 null] /D [null /XYZ 89.291 719.644 null] 4 0 obj IEEE Transactions on Information Theory, 13(1): 21-27. << >> << Nevala K (2017). /C [0 1 1] /F133 26 0 R <<56ECF4A7FD2F9C449ED11EB1A7D1618D>]/Prev 225910/XRefStm 2740>>
/D [null /XYZ 89.291 204.856 null] /H /I << Some studies in machine learning using the game of checkers. /Type /Action /Subtype /Link 0000113994 00000 n Prediction of Breast Cancer, Machine-learning approaches in drug discovery: methods and applications, Branch Selection Recommendation for Higher Secondary Student using Data Mining Techniques, A SURVEY ON DIFFERENT MACHINE LEARNING ALGORITHMS AND WEAK CLASSIFIERS BASED ON KDD AND NSL-KDD DATASETS, International Journal of Artificial Intelligence & Applications (IJAIA), Towards Detecting Crop Diseases and Pest by Supervised Learning, DESIGN AND REALIZATION OF ON-LINE, REAL TIME WEB USAGE DATA MINING AND RECOMMENDATION SYSTEM USING BAYESIAN CLASSIFICATION METHOD, Machine learning for email spam filtering: review, approaches and open research problems. 0000115129 00000 n 0000071987 00000 n
/H /I 0000016075 00000 n >> To browse Academia.edu and the wider internet faster and more securely, please take a few seconds toupgrade your browser. Induction of decision trees. << 3Department of Computer Sciences, University of Khartoum, Khartoum, Sudan, Corresponding author's ORCID profile:https://orcid.org/0000-0003-4263-168X, https://doi.org/10.21833/ijaas.2021.02.001. The academy is established to help players from Ghana and across Africa gain recognition and advance their football careers. /Type /Annot /Type /Action
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Adhatrao K, Gaykar A, Dhawan A, Jha R, and Honrao V (2013). Top 10 algorithms in data mining. /ToUnicode 36 0 R /A 4j!I84^CqhD=IIzFC8$qH5!i8$qX=IuzFC8$6qH5m4j!i8YCqhhnT"6sFEgPtVE\b#sz. /Type /Pages /F 4
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2018- Strikers FC Academy . /F 4 /Subtype /Link /Rect [237.491 161.232 291.238 171.631] /Rect [495.331 365.334 502.396 374.183] In the IEEE Recent Advances in Intelligent Computational Systems, IEEE, Trivandrum, India: 227-231. }8oxtc|wq/%1O7o_O/a|904We3}O?]]:J9wK >?Qeq]Y4|F7XJxsp+qo~j?lh0F&xku s:1&sA:ip$*s@`PV2$m2DDm!5QLTQ31{=If"iLADQ31'=Ifbz&FDAH5g"iL,FD(uH5TVL$%H5IfbIz&FDZlH5K34j&}&[N/J%&5IGLkVBQNzMT F/ $"^)DD&%EiC)6)Z Cdm %PDF-1.5 << >> All Rights Reserved Design & Developed By:: RINJAcom, For enquary We can help:: +233 (0) 24-611-9999. {GNw{zhm"h~ob4P.~mC]/@v1G,Q+p+lGpgw,,pLgslE:}XP $S0Z,^&g7W5X+{L7/weM):jO /C [0 1 1] la [,b-DkwB|[ 4B jp'v9P.7%z\uS:\yQFb~>;2|@)&q2}PI IPCVo"*U %fW[8vj01;"O>Jh0_VJQP ~[; )rZL}Og}(1\EH{rdFoBVd&S:uGu097k>;fiC/#Sj\y{_;=8cN 9$}|0rSX=8xE{X kq`bK}81p* >cq6aZst?ox~lhvdj0Lc;pu#M\M>2WoxM[_Yno;[9T?g5PKi#D)mtIn< iY0@nsEVHNNF Q)E4c$2S. /A SAS Institute, North Carolina, USA. A study on classification techniques in data mining. /C [0 1 0] /Rect [298.853 392.531 305.918 401.281] 0000013058 00000 n /C [0 1 0] 0000092581 00000 n /A /H /I Evaluation of decision tree pruning algorithms for complexity and classification accuracy.
hb```b`e`g`` l@Q%,7T$n/``U` TTStg:}!6L"}ZTW6HX4x|r~=;{sATm]rr7sOWd. <> International Journal of Computer and Electrical Engineering, 2(4): 660-665. Friedman N and Goldszmidt M (1996). We groom talented players with the right technical, tactical and mental skills to enable them to compete as professional players at the highest level in football anywhere. k``h g2 U# E9w0erb=Q,MYxp~;R!3c8dui~c"2M @ZNg ` p /Encoding 35 0 R
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>> >> /Rect [404.404 338.334 416.542 347.084] Data mining is also defined as the process of analyzing a quantity of data (usually a large amount) to find a logical relationship that summarizes the data in a new way that is understandable and useful to the owner of the data. << /H /I /F 4 aO[>vId\LP\F@LpyWEQDb:^9\G*F)rCO\3?.vO5ECHHd..DxG_! /URI (https://creativecommons.org/licenses/by/4.0) /S /GoTo startxref 24 0 obj Discretizing continuous attributes while learning Bayesian networks. X0a)I3xd.lM' +NPWDy@]awCT?r,'_x7H`s4\]XU Hx1@V-'=yhI`3}F!g(5G,^7(J>`)H 0000072255 00000 n
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>> /Border [0 0 0] Quinlan JR (1986). 0000114973 00000 n /URI (mailto:dperakovic@fpz.unizg.hr) Nearest neighbor pattern classification. /C [0 1 1] >> 0000093049 00000 n 0000041064 00000 n 0000004678 00000 n >> Efficient learning machines: Theories, concepts, and applications for engineers and system designers. 0000016969 00000 n << 234 0 obj <> endobj /Subtype /Link
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/S /URI endobj Kesavaraj G and Sukumaran S (2013). /Border [0 0 0] B!A!B << 14 0 obj /Annots [10 0 R 11 0 R 12 0 R 13 0 R 14 0 R 15 0 R 16 0 R 17 0 R 18 0 R 19 0 R 20 0 R 21 0 R 22 0 R 23 0 R] hz xTE{vIgt:[gCBE .*:*fkwp5(3&} }sS:U G}[~`P ,-[,$@;|veZ %Cjn=7:NpmoKHh4=ok>wuQY! For this reason, it is the view of the writer that further research needs to be carried out to explore the potential of combining several of these algorithms to solve machine learning problems. >> ;7dJb~"8-+!6o6cFfe&\6J@j==_Ac@zkG[o!qMADqI /D [null /XYZ 89.291 458.699 null] Bardab SN, Ahmed TM, and Mohammed TAA (2021). <> /C [0 1 0] /Type /Annot Emerging Artificial Intelligence Applications in Computer Engineering, 160(1): 3-24. /F 4 11 0 obj >> 0000115538 00000 n %PDF-1.4 % /Type /Annot 5 classification algorithms. % %%EOF 0000010646 00000 n /Border [0 0 0] ;mdlIx':84~"N5Z vh)KsB(|+>zv3!iM(SEM2!G endobj >> stream 0000009962 00000 n % /S /URI /Type /Annot 3 0 obj Predicting students' performance using ID3 and C4. xref This paper examines the various types of classification algorithms in Data Mining, their applications and categorically states the strengths and limitations of each type. % 2 0 obj
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/H /I Quinlan JR (1993). /LastChar 252 1 0 obj 1 0 obj /Border [0 0 0] 0000075820 00000 n Z{IRqF (P0f[j0d[00fxswE|w$ m.aKGU >> 0000003072 00000 n 0000082387 00000 n /Type /Action /S /GoTo endstream endobj 235 0 obj <> endobj 236 0 obj <>/ExtGState<>/Font<>/XObject<>>>/Rotate 0/Tabs/S/Type/Page>> endobj 237 0 obj <>stream endobj 0000005299 00000 n /Border [0 0 0] /A Volume 8, Issue 2(February 2021), Pages: 1-5, ----------------------------------------------, Title: Data mining classification algorithms: An overview, Author(s):Saeed Ngmaldin Bardab 1, *, Tarig Mohamed Ahmed 2, 3, Tarig Abdalkarim Abdalfadil Mohammed 1, 1Department of Computer Sciences, ALNeelain University, Khartoum, Sudan
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>> 0 0000002925 00000 n /H /I www.hindawi.com/journals/sp/2019/8706505/, Mohammad Shamsu Uddin, Guotai Chi +2 more, Copyright @ 2022 | PubGenius Inc. | Suite # 217 691 S Milpitas Blvd Milpitas CA 95035, USA, Comparison of Data Mining Classification Algorithms Determining the Default Risk, Data Mining Practical Machine Learning Tools and Techniques, Evaluating Data Mining Classification Methods Performance in Internet of Things Applications, A Novel Phase Space Reconstruction- (PSR-) Based Predictive Algorithm to Forecast Atmospheric Particulate Matter Concentration, A Detailed Study on Classification Algorithms in Big Data, Credit scoring with a data mining approach based on support vector machines, Prediction of default payment of credit card clients using Data Mining Techniques, An alternative statistical framework for credit default prediction, Estimation of loan applicants default probability applying discriminant analysis and simple bayesian classifier, The Application Study of Credit Risk Model In Financial Institution via Machine-learning Algorithms, Credit Risk Analysis Using Machine Learning Techniques.