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A Review Study on Data Mining Algorithms for Prediction Diseases

2020 International journal for research in engineering application & management  
This paper describes the various data mining algorithms such as neural network, support vector machine, KNN, decision tree etc. and provides an overall brief of the existing work.  ...  The major advantage of using data mining is that to identify the structures.  ...  The rules generated by the proposed system are important as Original Rules, Pruned Rules, rules without duplicates, Classified Rules, Sorted Rules and Polish.  ... 
doi:10.35291/2454-9150.2020.0340 fatcat:z4clbq7lvbc5pf5rucdlt7gh7a

A STUDY OF DM TECHNIQUES IN SOFT COMPUTING FRAMEWORK

RK Dhuware, SR Pande, SJ Sharma
2018 International Journal of Advanced Research  
Overview of Knowledge Discovery and Data Mining:-KDD focuses on the overall process of knowledge discovery from large volumes of data, including the storage and accessing of such data, scaling of algorithms  ...  Fuzzy sets provide a natural framework for the process in dealing with uncertainty. Neural networks and Rough sets are widely used for classification and rule generation.  ...  Wei and Chen have mined generalized association rules with fuzzy taxonomic structures. Fuzzy logic is useful for data mining systems performing classification such as CRM, Health care and finance.  ... 
doi:10.21474/ijar01/6834 fatcat:ez3i6rcihrgbjnkbpe7he6dbwq

Application of data mining techniques in customer relationship management: A literature review and classification

E.W.T. Ngai, Li Xiu, D.C.K. Chau
2009 Expert systems with applications  
Despite the importance of data mining techniques to customer relationship management (CRM), there is a lack of a comprehensive literature review and a classification scheme for it.  ...  On the other hand, classification and association models are the two commonly used models for data mining in CRM.  ...  Common tools used for classification are neural networks, decision trees and ifthen-else rules.  ... 
doi:10.1016/j.eswa.2008.02.021 fatcat:nqlw5dkqjzfhpf2cldlmoxd25e

A Case Study of Predicting Banking Customers Behaviour by Using Data Mining

Xujuan Zhou, Ghazal Bargshady, Moloud Abdar, Xiaohui Tao, Raj Gururajan, KC Chan
2019 2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)  
Two typical data mining techniques -Neural Network and Association Rules -are applied to predict the behavior of customers and to increase the decision-making processes for recalling valued customers in  ...  In this research, a new Customer Knowledge Management (CKM) framework based on data mining is proposed.  ...  The neural networks and association rule mining are used as two classification techniques in this study.  ... 
doi:10.1109/besc48373.2019.8963436 dblp:conf/besc/ZhouBATGC19 fatcat:a3o75yoftfa7tftagjrnwcbsnu

An Improved K Nearest Neighbor Classifier Using Interestingness Measures For Medical Image Mining

J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar
2013 Zenodo  
In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification.  ...  Feature weights are calculated using the interestingness measures used in association rule mining.  ...  Mittal, the Director of BITS Pilani, Dubai Campus for his encouragement and support in facilitating this research.  ... 
doi:10.5281/zenodo.1087652 fatcat:hilnkarx6jg6rdgtaaztnwyuyy

A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

Anuj Sharma, Prabin Kumar Panigrahi
2012 International Journal of Computer Applications  
This paper presents a comprehensive review of the literature on the application of data mining techniques for the detection of financial accounting fraud and proposes a framework for data mining techniques  ...  to the problems inherent in the detection and classification of fraudulent data.  ...  A classification framework for financial fraud is suggested in [7] based on the financial crime framework of the U.S.  ... 
doi:10.5120/4787-7016 fatcat:ifmqadjmwfeufi57cizszqhgzy

Prevention and Detection of Financial Statement Fraud – An Implementation of Data Mining Framework

Rajan Gupta, Nasib Singh
2012 International Journal of Advanced Computer Science and Applications  
In this study we implement a data mining methodology for preventing fraudulent financial reporting at the first place and for detection if fraud has been perpetrated.  ...  The association rules generated in this study are going to be of great importance for both researchers and practitioners in preventing fraudulent financial reporting.  ...  In the next stage of the framework, Rule engine generates the required association rules. In the process of rule generation, frequent itemsets is being generated using FP Growth.  ... 
doi:10.14569/ijacsa.2012.030825 fatcat:2vqh5jpdefh3vbe6lf72fykxsy

A Framework for Implementing Machine Learning algorithms using Data sets

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Design and Implementation of a framework that is associated with different machine learning algorithms.  ...  framework.  ...  Apriori is a classical algorithm for mining association rules. D.  ... 
doi:10.35940/ijitee.k1263.0981119 fatcat:m5u3gebolbhpdjwo2pbeaqanvq

A Data Mining Framework for Prevention and Detection of Financial Statement Fraud

Rajan Gupta, Nasib Singh Gill
2012 International Journal of Computer Applications  
In this paper we propose a data mining framework for prevention and detection of financial statement fraud.  ...  In the wake of failure of many organisations, there is a dire need of prevention and detection of financial statement fraud.  ...  The rule engine module of our framework mines the dataset for generating association rules. In the process of association rule generation rule engine first find the frequent itemset.  ... 
doi:10.5120/7789-0889 fatcat:3tcdhglr7batpmkirbg3ndo7li

The Estimation of Wind Velocity Using Data Mining Techniques

Sattar Nabee Rasool, Ahmet Koca, Karwan Hussein Qader
2017 Qalaai Zanist Scientific Journal  
In this paper, we proposed a framework that exploits data mining techniques such as J48, KNN, Neural Networks, SVM and Linear Regression.  ...  The framework takes climate dataset as input, completes training phase and makes different models using data mining algorithms.  ...  They used a general framework to cater to the needs of analysis of uncertain data.  ... 
doi:10.25212/lfu.qzj.2.2.44 fatcat:zc6mjnztvfc4bcdlswr6hag444

Generalizations of Rough Sets: From Crisp to Fuzzy Cases [chapter]

Masahiro Inuiguchi
2004 Lecture Notes in Computer Science  
Context of Knowledge Discovery Problems p. 192 GAMInG -A Framework for Generalization of Association Mining via Information Granulation p. 198 Mining Un-interpreted Generalized Association Rules  ...  Association Rules p. 610 Pattern Mining for Time Series Based on Cloud Theory Pan-concept-tree p. 618 Using Rough Set Theory for Detecting the Interaction Terms in a Generalized Logit Modelp. 624  ... 
doi:10.1007/978-3-540-25929-9_3 fatcat:saiacsrpovgphlh5zzhoq4tcrq

A platform for wide scale integration and visual representation of medical intelligence in cardiology: the decision support framework

T.P. Exarchos, M.G. Tsipouras, D. Nanou, C. Bazios, Y. Antoniou, D.I. Fotiadis
2005 Computers in Cardiology, 2005  
An initial set of crisp rules, generated using data mining techniques, is employed to define a fuzzy model, using the sigmoid function and fuzzy equivalents of the binary operators.  ...  The core of the NOESIS project is a set of Fuzzy Expert Systems (FES), one for each cardiovascular sub-domain, automatically generated from the DSF.  ...  Acknowledgements This research is part funded by the program "Heraklitos" of the Operational Program for Education and Initial Vocational Training of the Hellenic Ministry of Education and by the European  ... 
doi:10.1109/cic.2005.1588062 fatcat:tnb3dpi44fe57pxeew536d5mmu

A Review of Cyber Attack Classification Technique Based on Data Mining and Neural Network Approach
English

Bhavna Dharamkar, Rajni Ranjan Singh
2014 International Journal of Computer Trends and Technology  
Data mining offers various techniques such as clustering, classification, rule generation and temporal event mining; these techniques are very efficient for detection process of cyber attack.  ...  These framework and proposed method is based on data mining and neural network approach.  ...  Data mining offer various technique for classification such as KNN, decision tree, SVM and rule based classification; all these classification promise the result of classification.  ... 
doi:10.14445/22312803/ijctt-v7p106 fatcat:ppzo3ygvn5hlla5x5cha62yi6m

Research of Chronic Kidney Disease based on Data Mining Techniques

2019 International journal of recent technology and engineering  
Different information mining strategies, for example, bunching, characterization, affiliation investigation, relapse, outline, time arrangement examination and succession investigation were utilized to  ...  Kidney disease is one of the real general medical issues these days. Ceaseless ailments prompt to horribleness and mortality in India and furthermore in the low pay and center nation.  ...  Three different neural network models have been implemented for chronic kidney disease prediction which includes back propagation neural network, generalized feed forward neural network and modular neural  ... 
doi:10.35940/ijrte.b1019.0982s1119 fatcat:6hgfgms67ff3bnkdlc6memsonu

Image mining framework and techniques: a review

Nilanjan Dey, Wahiba Ben Abdessalem Karâa, Sayan Chakraborty, Sukanya Banerjee, Mohammed A.M. Salem, Ahmad Taher Azar
2015 International Journal of Image Mining  
Image mining refers to a data mining technique where images are used as data.  ...  This review paper presents a detailed view on the existing research works in the area of image mining and also summarised the different techniques used.  ...  , image clustering, association rule mining, and neural network.  ... 
doi:10.1504/ijim.2015.070028 fatcat:kszujsxburaxxkbqjeh5gwbmbi
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