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Incremental classification using Feature Tree [article]

Nishant Vadnere, R.G.Mehta, D.P.Rana, N.J.Mistry, M.M.Raghuwanshi
2014 arXiv   pre-print
In many applications of data stream mining data can be read only once or a small number of times using limited computing and storage capabilities.  ...  In recent years, stream data have become an immensely growing area of research for the database, computer science and data mining communities. Stream data is an ordered sequence of instances.  ...  A brief review of related work is given in Section II which includes preprocessing, data mining algorithm for Trie structure and classification.  ... 
arXiv:1402.1257v2 fatcat:qni7g33mjbbpzhzflw7nxlb4l4

Identifying and Analysis of Scene Mining Methods Beased on Scenes Extracted Features [article]

Ashraf Sadat Jabari, Mohammadreza Keyvanpour
2012 arXiv   pre-print
Scene mining can be followed by identifying scene mining components and representing a framework to analyzing and evaluating methods.  ...  Finally, these methods are analyzed and evaluated via a proposal framework.  ...  Related work Semantic scene classification is categorizing scenes into a discrete set of classes. In scene mining is determined which semantic class, a scene is belong to (sky, street, beach).  ... 
arXiv:1201.1668v1 fatcat:iztacsucsnhqdbw2ucwn5h2exq

A model driven framework for geographic knowledge discovery

O. Glorio, J. Zubcoff, J. Trujillo
2009 2009 17th International Conference on Geoinformatics  
Geographic knowledge discovery (GKD) is the process of extracting information and knowledge from massive georeferenced databases.  ...  To overcome these pitfalls, in this paper, we propose a modeling framework that addresses the development of the different parts of a multilayer GKD process.  ...  Mancha Ministry of Education and Science (Spain).  ... 
doi:10.1109/geoinformatics.2009.5293412 fatcat:kavn2236nbgv3pjpjf5nwzz2ka

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  
NOESIS addresses wide scale integration and visual representation of medical intelligence in cardiology and aims at the development of a web-based personalized system with enhanced intelligence that supports  ...  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.  ...  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

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.  ...  With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis.  ...  Mittal, the Director of BITS Pilani, Dubai Campus for his encouragement and support in facilitating this research.  ... 
doi:10.5281/zenodo.1087652 fatcat:hilnkarx6jg6rdgtaaztnwyuyy

An Educational Data Mining System For Advising Higher Education Students

Heba Mohammed Nagy, Walid Mohamed Aly, Osama Fathy Hegazy
2013 Zenodo  
In our research, we propose a "Student Advisory Framework" that utilizes classification and clustering to build an intelligent system.  ...  Machine learning can be applied to solve different regression, classification, clustering and optimization problems.  ...  Section Three presents related works in educational data mining. Section Four introduces the proposed intelligent framework for a student advisory system.  ... 
doi:10.5281/zenodo.1088158 fatcat:beopv4nvsvflba5pcrvhlhdb5u

Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach [chapter]

Michelangelo Ceci, Annalisa Appice, Donato Malerba
2004 Lecture Notes in Computer Science  
The method is implemented in a Data Mining system tightly integrated with an object relational spatial database.  ...  Classification is probabilistic and is based on an extension of naïve Bayes classifiers to multi-relational data.  ...  (Spatial Mining for Data of Public Interest).  ... 
doi:10.1007/978-3-540-30116-5_12 fatcat:yy2eo6ux4ndwrpzzlxwriavfiy

An Overview of Object-Oriented Frameworks with Application in Spatio temporal Data Mining

K. Venkateswara Rao, A. Govardhan, K.V. Chalapati Rao
2011 CVR Journal of Science and Technology  
So there is a need to develop a framework that takes care of common requirements at analysis and design level so that spatiotemporal data mining applications can be built through software reuse.  ...  An object-oriented framework is a reusable software system providing large scale reuse, including reuse of analysis and design.  ...  The research community in spatiotemporal databases could develop conceptual models for spatiotemporal databases, and techniques to implement these models in object-relational and relational database systems  ... 
doi:10.32377/cvrjst0102 fatcat:2cryaepyzvderidxjfxopqcz4q

Privacy Protection in Data Mining

Jinquan Li, Michael J. Shaw, Fu-ren Lin
2003 Americas Conference on Information Systems  
In this paper, we present a framework for privacy-enhancing data mining and develop such privacy-enhancing technologies as attribute selection, discretization, fixed-data perturbation, probability distribution  ...  Specifically, we address the issue of privacy protection through using the attribute selection, discretization, and randomization techniques and give an example of inducing the decisiontrees from training  ...  A Framework for Privacy-Enhancing Data Mining In Figure 1 , we show a framework for privacy-enhancing data mining. This framework consists of the following components: Data.  ... 
dblp:conf/amcis/LiSL03 fatcat:7bsfbkksrnd4befrz56ccn5vga

Mining Relational Association Rules for Propositional Classification [chapter]

Annalisa Appice, Michelangelo Ceci, Donato Malerba
2005 Lecture Notes in Computer Science  
Propositionalisation based on relational association rules discovery is implemented in a relational classification framework, named MSRC, tightly integrated with a relational database.  ...  In principle, relational data can be transformed into propositional one by constructing propositional features and performing classification according to some robust and well-known propositional classification  ...  Acknowledgments We thank Simon Rawles and Peter Flach for working together in defining and developing the REFER algorithm.  ... 
doi:10.1007/11558590_53 fatcat:ngj2cb2btfao3ibxyvg3mss2oi

Mining Signatures from Event Sequences

Rajput S.H., Chetan Jadhav, Yogesh Deshmukh, Sandip Sonawane, Hemant Jadhav
2015 IJARCCE  
This paper proposes a novel secular knowledge representation and learning framework to proposed largescale secular signature mining of longitudinal heterogeneous occasional data.  ...  The framework allows the presentation, extra4ction, and mining of high order latent occasion event structure and relationships between single and many sequences.  ...  CONCLUSION In this paper, we have presented a novel secular event matrix representation and learning framework in conjunction with an in-depth validation on both constructed and real world datasets.  ... 
doi:10.17148/ijarcce.2015.44129 fatcat:up6onqghvje7rgj6bi4o4aw7ky

A Heart Disease Prediction Model using Logistic Regression

K. Sandhya Rani, M. Sai Manoj, G. Suguna Mani
2018 International Journal of Trend in Scientific Research and Development  
This paper proposes a rule based model to compare the accuracies of applying rules to the individual results of logistic regression on the Cleveland Heart Disease Database in order to present an accurate  ...  The early prognosis of cardiovascular diseases can aid in making decisions to lifestyle changes in high risk patients and in turn reduce their complications.  ...  The pre-processed data is classified with Regression The term regression can be defined as the measuring and analyzing the relation between one or more independent variable and dependent variable.  ... 
doi:10.31142/ijtsrd11401 fatcat:qbvkaryeljb3vg2rgicuc4jhda

Exploring multi-relational temporal databases with a propositional sequence miner

Carlos Abreu Ferreira, João Gama, Vítor Santos Costa
2015 Progress in Artificial Intelligence  
With this framework we mine each class partition individually and we do not use classical aggregation strategies, like window aggregation.  ...  In this work we introduce the MuSer, a propositional framework that explores temporal information available in multi-relational databases.  ...  When dealing with continuous attributes, first we apply a discretization strategy and then proceed in the same way we do for discrete attributes.  ... 
doi:10.1007/s13748-015-0065-x fatcat:bjdmkpa77va4hgwhju5p7j4mpy

Genre cataloging and instrument classification in large databases using music mining approach

2016 International Journal of Latest Trends in Engineering and Technology  
The classification through wavelet infuses mining instantaneous frequency of music information, mounting highlights with sub-band coefficients and spatial-temporal energy location curve.  ...  In Mining of music information, characterization tasks are subdivided into genre cataloging, instrument distinguishing and artist classification.  ...  The explore displayed in this paper is an attempt to design, implement, and evaluate a genre and instrument characterization framework for a music database.  ... 
doi:10.21172/1.72.577 fatcat:puklz62i4vcbrndomvrxhpeuc4

Application and Assessment of Classification Techniques on Programmers' Performance in Software Industry

Sangita Gupta, Suma V.
2015 Journal of Software  
One of the strategies is to process and analyze previous data of software companies to predict future failures. Data mining techniques have the ability to uncover hidden patterns in large databases.  ...  Software companies can build models that predict with a high degree of accuracy the attributes required in human aspect for success.  ...  Data mining techniques have proved to be a promising tool to extract knowledge and reveal patterns from the databases related to project personnel.  ... 
doi:10.17706//jsw.10.9.1096-1103 fatcat:43tpc4wgyvexpb5otqpqla3wsq
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