data mining research papers 2012 section 3







Foundation of mining class-imbalanced data
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Mining class-imbalanced data is a common yet challenging problem in data mining and machine learning. When the class is imbalanced, the error rate of the rare class is usually much higher than that of the majority class. How many samples do we need in order to

A Review of Financial Accounting Fraud Detection based on Data Mining Techniques
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Abstract With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries. The failure of internal auditing

Review of Data Mining Techniques in Cloud Computing Database
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ABSTRACT Data mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It is the extraction of information from huge volume of data or set through the use of various data mining techniques. The data mining

A Complete Data Mining process to Manage the QoS of ADSL Services
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Abstract. 1 In this paper we explore the interest of computational intelligence tools in the management of the Quality of Service (QoS) for ADSL lines. The paper presents the platform and the mechanisms used for the monitoring of the quality of service of the Orange ADSL

A Data Mining Approach to Comparing American and Canadian Grade 10 Students PISA Science Test Performance
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ABSTRACT According to 2006 Programme for International Student Assessment (PISA), sixteen Organization for Economic Cooperation and Development (OECD) countries had scores that were significantly higher than the US. The top three performers were Finland,

Hybrid Approach of Data Mining Techniques, PCA, EDM and SVM for Cancer Gene Feature Selection and Classification
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ABSTRACT Microarrays are a significant advance both because they may contain a very large number of genes and of their small size. DNA microarray technology has in a decade been rapidly adopted by biomedical researchers and emerged as a very prominent research

Mining Association Rule in Classified Data for Course Recommender System in E-Learning
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 KEY WORDS ADTree Classification algorithm, Apriori Association Rule algorithm, Weka 1. INTRODUCTION Data mining also known as Knowledge Discovery in Database (KDD) is the extraction of interesting (non-trivial, implicit, previously unknown and potentially useful

A study of data mining trend through the optimized bibliometric methodology based on SCI database from 1993 to 2011
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ABSTRACT An optimized bibliometric method was applied in this work to evaluate global scientific production of data mining papers of the Science Citation Index (SCI). In compared with traditional bibliometric keyword analysis, a semantic words class was established by

Comparing apples and oranges: measuring differences between exploratory data mining results
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Abstract Deciding whether the results of two different mining algorithms provide significantly different information is an important, yet understudied, open problem in exploratory data mining. Whether the goal is to select the most informative result for analysis, or to decide

Use of Data Mining in Emergency Evacuation Planning
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ABSTRACT Evacuating large numbers of people during a natural disaster or terrorist attack is a vital challenge for emergency management professionals. This is even a continuous pressure on the management in the hurricane zones. Hurricanes Katrina and Rita vividly

Unsupervised data mining technology based on research of stroke medication rules and discovery of prescription
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For collecting and sorting literature on treatment of ancient and modern stroke at the entry point, frequency and charts analysis methods were applied. Modern computer technology and statistics were used to do in-depth study of stroke literature data, explore stroke

Rattle and Other Data Mining Tales
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My own voyage to data mining started long before data mining had a name. It started as a curiosity that a young scientist had in searching for interesting patterns in data. In fact, the journey began in 1983 as an artificial intelligence Ph. D. student at the Australian National

Prediction of Churn Behavior of Bank Customers Using Data Mining Tools
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ABSTRACT The customer churn is a common measure of lost customers. By minimizing customer churn a company can maximize its profits. Companies have recognized that existing customers are most valuable assets. Customer retention is critical for a good

Data Mining Office Behavioural Information from Simple Sensors
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Abstract This paper discussed the concept of using three simple sensors to monitor the behavioural patterns of an office occupant. The goal of this study is to capture behaviour information of the occupant without the use of invasive sensors such as cameras that do

Mining Spatially Co-Located Objects from Vehicle Moving Data
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 Mining Spatially Co-Located Objects from Vehicle Moving Data  Mining co-location patterns from spatial databases may disclose the types of spatial features which are likely located as neighbors in space.

A Hybrid Data Mining based Intrusion Detection System for Wireless Local Area Networks
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ABSTRACT The exponential growth in wireless network faults, vulnerabilities, and attacks make the WLAN security management a challenging research area [29]. Data mining applied to intrusion detection is an active area of research. The main reason for using data

and Proteomic Phylogenetic Analysis of Indian Isolate of Partial Coat Protein Gene Sequence of Zucchini Yellow Mosaic Virus (ZYMV) Using Data Mining
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Data Mining DICOM RT objects for quality control in radiation oncology
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ABSTRACT Our goal in this paper is to data mine the wealth of information contained in the dose-volume objects used in external beam radiotherapy treatment planning. In addition, by performing computational pattern recognition on these mined objects, the results may help

Improved Study of Heart Disease Prediction System using Data Mining Classification Techniques
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ABSTRACT The Healthcare industry is generally information rich, but unfortunately not all the data are mined which is required for discovering hidden patternseffective decision making. Advanced data mining techniques are used to discover knowledge in database

Final Report on Video Log Data Mining Project
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16Abstract This report describes the development of an automated computer vision system that identities and inventories road signs from imagery acquired from the Kansas Department of Transportation s road profiling system that takes images every 26.4 feet on

Intelligent Data Mining Techniques for Intrusion Detection Models on Network
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ABSTRACT Data mining techniques have been successfully applied in almost all the fields including process control, marketing, manufacturing, fraud detection and network management. Over the past few years, a growing number of research projects have

Toward a methodology for agent-based data mining and visualization
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We explore the notion of agent-based data mining and visualization as a means for exploring large, multi-dimensional data sets. In Reynolds classic flocking algorithm (1987), individuals move in a 2-dimensional space and emulate the behavior of a flock of birds (or

Nonhypothesis-Driven Research: Data Mining and Knowledge Discovery
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Clinical information, stored over time, is a potentially rich source of data for clinical research. Knowledge discovery in databases (KDD), commonly known as data mining, is a process for pattern discovery and predictive modeling in large databases. KDD makes extensive use

An appropriate pattern to solving a parallel machine scheduling by a combination of meta-heuristic and data mining
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ABSTRACT Scheduling problems applications in nowadays competitive world and the rate of their result s usage in industrial area demonstrate the importance of this problem. In this article, an identical parallel machine by the objective function of total weighted tardiness is

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data mining using classifications

Classifying the network intrusion attacks using data mining classification methods and their performance comparison
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Abstract Security is becoming a critical part of organizational information systems. Intrusion Detection System (IDS) is an important detection that is used as a countermeasure to preserve data integrity and system availability from attacks. The main reason for using

Realization of data mining model for expert classification using multi-scale spatial data
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ABSTRACT: Data mining models show great efficiency on acquiring knowledge for expert system classification. This study aimed at mining knowledge contained in landscape from multi-scale spatial data using decision tree learning model and evaluating the

Soil classification using data mining techniques: a comparative study
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Abstract: Soil Classification deals with the systematic categorization of soils based on distinguished characteristics as well as criteria. We developed Data Mining techniques like: GATree, Fuzzy Classification rules and Fuzzy C-Means algorithm for classifying soil

Diagnosis of lung cancer prediction system using data mining classification techniques
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Abstract:Cancer is the most important cause of death for both men and women. The early detection of cancer can be helpful in curing the disease completely. So the requirement of techniques to detect the occurrence of cancer nodule in early stage is increasing. A

Classification and mining of brain image data using adaptive recursive partitioning methods: application to Alzheimer disease and brain activation patterns
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Purpose: To effectively identify discriminative spatial areas in MRI and fMRI and make image classification, similarity searches and mining of associations between spatial distributions and other clinical assessment feasible we have developed brain informatics tools that are

Student performance prediction by using data mining classification algorithms
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Abstract:This paper presents the results from data mining research, performed at one of the famous and prestigious Bulgarian universities, with the main goal to reveal the high potential of data mining applications for university management and to contribute to more efficient

Component Classification and Retrieval Using Data Mining Techniques
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Abstract A significant hurdle confronts the software reuser attempting to select candidate components from a software repositorydiscriminating between those components without resorting to inspection of the implementation (s). In this paper We discuss data mining

Medical image classification using an efficient data mining technique
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Abstract Data mining refers to extracting or mining knowledge from large amounts of data. It is an increasingly popular field that uses statistical, visualization, machine learning, and other data manipulation and knowledge extraction techniques aimed at gaining an insight

Pattern clustering of forest fires based on meteorological variables and its classification using hybrid data mining methods
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This paper outlines two hybrid approaches to investigate the nonlinear relationship between size of a forest fire and meteorological variables (temperature, relative humidity, wind speed and rainfall). Self organizing map was used to cluster the historical meteorological

Classification of Al-Hadith Al-Shareef using data mining algorithm
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Abstract In this paper we compared the effectiveness of four different automatic learning algorithms for classifying Al_Hadith Al_Shareef into 8 selective books depending on Sahih BuKhari. The automatic learning algorithms are Rocchio algorithm, K-NN algorithm (K-

Using GNUsmail to Compare Data Stream Mining Methods for On-line Email Classification.
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Abstract Real-time classification of emails is a challenging task because of its online nature, and also because email streams are subject to concept drift. Identifying email spam, where only two different labels or classes are defined (spam or not spam), has received great

Classification of herbal gardens in India using data mining
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ABSTRACT There are a large number of herbal gardens in India and most of them are not linked and classified the availability of medicinal plant species of these gardens. In this study, the hierarchical clustering technique of data mining was applied on the herbal

A personalized classification of employment offers using data mining methods
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Abstract:In this paper we describe a method designed for filtering the information available on job portals, according to users' preferences. We started by collecting the information needed crawling the specialized web sites, in order to build the necessary dataset.

Performance Analysis of Engineering Students for Recruitment Using Classification Data Mining Techniques
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Abstract---Data Mining is a powerful tool for academic intervention. Mining in education environment is called Educational Data Mining. Educational Data Mining is concerned with developing new methods to discover knowledge from educational database and can used

Rule Based Classification System for Medical Data Mining Using Fuzzy Ant Colony Optimization
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Ant algorithms are based on the cooperative behavior of real ant colonies, which are able to find the shortest path from a food source to their nest [2]. While walking, real ants deposit a chemical substance called pheromone on the ground. Ants can smell pheromone and

Mining customer data for decision making using new hybrid classification algorithm
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ABSTRACT Classification and patterns extraction from customer data is very important for business support and decision making. Timely identification of newly emerging trends is needed in business process. Sales patterns from inventory data indicate market trends

Star-Galaxy Classification Using Data Mining Techniques with Considerations for Unbalanced Datasets
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Abstract. We used a range of data-mining techniques in an effort to improve the classification of stars and galaxies for imaging data from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS), and extracted with SExtractor. We found that the Artificial Neural

A Comparative Study of Classification Methods in Data Mining using RapidMiner Studio
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Abstract:Data mining is the knowledge discovery process which analyses the large volumes of data from various aspects and summarizing it into useful information; data mining has become an essential and important component in various fields of daily life. It is used

Classification of Dengue Outbreak Using Data Mining Models
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ABSTRACT This paper presents the Malaysian dengue outbreak detection model using three classification methods. Dengue outbreak detection and prediction has been a major interest of researchers in surveillance and public health. In this paper, a selection of

Urban land cover classification with WorldView-2 images using data mining and Object-Based Image Analysis
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ABSTRACT: The products available from new satellite sensor systems with high spatial resolution present a considerable potential for applications in urban areas. These datasets open new perspectives for the automatic extraction of information for environmental

A Study Paper on IDS Attack Classification Using Various Data Mining Techniques
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Abstract Over the past several years, the Internet environment has become more complex and untrusted. Enterprise networked systems are inevitably exposed to the increasing threats posed by hackers as well as malicious users internal to a network. IDS technology

Intrusion Detection and Classification Using Improved ID3 Algorithm of Data Mining
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Abstract:Intrusion detection technology exists a lot of problems, such as low performance, low intelligent level, high false alarm rate, high false negative rate and so on. There is a need to develop some robust decision tree in order to produce effective decision rules The applications of data mining in engineering and manufacturing are enormous and useful for helping in the analysis of large data and information repositories for the discovery of trends, patterns and knowledge. In industrial engineering and manufacturing systems, the

Classification by object recognition in satellite images by using data mining
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Abstract:In this paper, an approach for classification of satellite images has been presented. Satellite images are rich in geographical information. Geographical information can be used in a number of ways. Our purposed system does classification of satellite

Model to Predict Price Movement of GWAR for North Gujarat Using Classification Rules: AData Mining Approach
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ABSTRACT: Research paper is based on decision tree (induction algorithm) which generates classification rules that will help in knowing next day price movement of the crop. The research paper provides a glimpse of the market and selling tips. We have used

Hypertension Interventions using Classification Based Data Mining
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Abstract: In the present study, we would like to gain the insight of the medical data through classification based data mining technique. The data sets of NCD (Non Communicable Diseases) risk factors, a standard report of Saudi Arabia 2005, in collaboration with WHO (

Image Classification using Hybrid Data Mining Algorithms–A Review
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Abstract:Data mining is one of the most significant research area in computer science. It is a calculation process of finding and determining valuable information from huge data set. Image classification is an important technique to generate valuable information. The

Data Mining: Evaluating Performance of Employee's using Classification Algorithm Based on Decision Tree
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Abstract---The ability to predict a employee's performance is very important in industrial Sector. Employee's performance is based upon diverse factors like personal, social, skills, punctuality, dependability, Interpersonal relation, task/responsibility, Work standard, actual

Analysis of Bayes, Neural Network and Tree Classifier of Classification Technique in Data Mining using WEKA
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ABSTRACT In today's world, gigantic amount of data is available in science, industry, business and many other areas. This data can provide valuable information which can be used by management for making important decisions. But problem is that how can find

An Effective Performance of Feature Selection with Classification of Data Mining UsingSVM Algorithm
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Abstract---This paper proposes one method of feature selection by using Support Vector Machine. The purpose of the proposed method is to reduce the computational complexity and increase the classification accuracy of the selected feature subsets. The dependence

A Proactive Anti-Phishing Tool Using Fuzzy Logic and RIPPER Data Mining ClassificationAlgorithm
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Novel Examination scenarios for U Learning using CharacteristicDiagrams S. Madhavi, Hye-jin Kim Prof. Chin-Chen Chang Chair Professor, IEEE and IET Fellows Department of

An Efficient KNN Classification by using Combination of Additive and Multiplicative DataPerturbation for Privacy Preserving Data Mining
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Abstract: Nowadays there is huge amount of data being collected and stored in databases everywhere across the globe. Recently, there has been a growing interest in the data mining area, where the objective is the discovery of knowledge that is correct and of high benefit

Comparative Study of Classification Algorithms Using Data Mining
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ABSTRACT Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis. Data mining uses sophisticated mathematical algorithms to segment the data and evaluate the probability of

Analysis of Adult-Onset Diabetes Using Data Mining Classification Algorithms
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ABSTRACT-Diabetes Mellitus is one of the most serious health challenges in both developing and developed countries. In the medical field a predictive data mining is used to diagnose the disease at the earlier stage which helps the physicians in the treatment

CLASSIFICATION OF DEFORESTATION FACTORS USING DATA MINING TECHNIQUES
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ABSTRACT Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries. Classification of deforestation is one of the primary objectives in the analysis of

A NEW METHODOLOGY FOR CLASSIFICATION IN DATA MINING USING BINARY CODED CLASSIFIERS
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ABSTRACT The accuracy of the learned classification rules in data mining is affected by the used learning algorithm and the availability of the whole training set in main memory during the learning process. In this paper, we propose a combination of data reduction

Land Cover Classification and Winter Wheat Mapping Using Data Mining Strategy
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Abstract: With the increasing sensors available, the knowledge gap between satellite data and application needs is continuously increasing. Aimed at the information demands for mapping land resources, a study on the key technologies of intelligent information

Data Mining Techniques Using WEKA classification for Sickle Cell Disease
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Abstract-Data mining is an inter-disciplinary promising field that focuses on access of information useful for high-level decisions and also includes Machine Learning. Data miners evaluate and filter the data as a result convert this data to information and information to

Classification of Jujube Fruits Using Different Data Mining Methods
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Abstract: In the current study, the qualitative grade of jujube fruit was evaluated using machine vision and classifying techniques. Images from four different classes of jujubes (G1, G2, G3, and G4), representing the quality grades of jujube fruits, were acquired using a

A New Discretization and Pattern Selection Method For Classification in Data Mining UsingFeedforward Neural Networks
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Abstract. This paper proposes a new supervised mean wise discretization algorithm and pattern selection method. A new supervised mean discretization algorithm automates the discretizatitarget

A Literature Review on Kidney Disease Prediction using Data Mining ClassificationTechnique
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Abstract---The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these mounds of data into useful information This paper describes a method of hybrid classifier/recogniser based on Neuro-Genetic processing of face images. The use of Data Mining techniques has a legitimate and enabling ways to explore large image collections using the Neuro-Genetic approaches.

Study of Various Classification Algorithms using Data Mining
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Terminology across fields is quite varied. In statistics, where classification is often done with logistic regression or a similar procedure, the properties of observations are termed explanatory variables (or independent variables, regressors, etc.), and the categories to

Mining Social Networking Data for Classification Using Reptree
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Abstract: On various social media sites, students discuss and share their everyday encounters in an informal and casual manner. Analyzing such data, however, can be challenging. The complexity of students' experiences reflected from social media content

A Classification of Spirometric Pattern and Modeling Using Statistical Data Mining
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Abstract:Respiratory disease is a medical term that encompasses pathological conditions affecting the organs and tissues. A lungs disease affects health condition of many people. Lungs diseases can be curable in early detection. Spirometry is valuable for diagnosing

Classification Based on Discrimination Prevention Using Data Transformation Techniques inData Mining
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Abstract-Data mining is a technique used to extract information from dataset and transforms it into understandable structure. In classification, discrimination is the major aspects in data mining. Discrimination is a type of treatment that includes denying the membership in one

Finding similar case subset and hotspot detection in felonious data set using data miningalgorithms: Weighted Clustering and classification
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Abstract Felonious activities have been increased terrifically. So safety has become a key issue to the societies. The control activities should be taken by the Security agencies (like FBI, CBI, CID, police Department and other law enforcement agencies). The security

Fast Distance Metric Based Data Mining Techniques Using P-trees: k-Nearest-NeighborClassification and k-Clustering
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Data mining on spatial data has become important due to the fact that there are huge volumes of spatial data now available holding a wealth of valuable information. Distance metrics are used to find similar data objects that lead to develop robust algorithms for the

CLASSIFICATION OF ELECTRICITY CUSTOMERS BASED ON REAL CONSUMPTION VALUES USING DATA MINING AND MACHINE LEARNING
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Classifying electricity customers based on real power consumptions has been particularly important in the last decade following the liberalization of the electricity markets in numerous countries and ubiquitous use of Automatic Meter Reading devices that collect

Effective Evaluation of Classification of Indian News Using Various Data Mining Algorithm
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ABSTRACT Classification may refer to categorization, the process in which ideas and objects are recognized, differentiated, and understood. Classification is an important data mining technique with broad applications. It classifies data of various kinds. Recent

Classification of Hearing Losses Determined Through the use of Audiometry using Data Mining Techniques
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Abstract Hearing is the sensory channel and critical ability for a man. The hearing test provides an evaluation of the sensitivity of a person's sense of hearing and is most often performed by an audiologist using an audiometer. An audiometer is used to determine a

Advances in Document Classification Using Data Mining
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Abstract-Document Classification is to assign a document to one or more classes or categories. This can be done either manually or by automation. However, since there is quintillion of data generated each year, we prefer to go with mining techniques in order to

First Semester Computer Science Students' Academic Performances Analysis by Using Data Mining Classification Algorithms
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Abstract The research on educational field that involves Data Mining techniques is rapidly increasing. Applying Data Mining techniques in an educational environment are known as Educational Data Mining that aims to discover hidden knowledge and patterns about

Classification of Smoking Cessation Status Using Various Data Mining Methods
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Today data mining is one of the most popular and most exciting disciplines of applied informatics. It enables us to discover complex and hidden patterns in data, which can potentially bring to totally new conclusions in different disciplines, where sometimes even

CLASSIFICATION OF E-COMMERCE DATA USING DATA MINING
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Abstract This paper discuss the development of an application for both consumers and companies, which would make use of information available on E-commerce websites to classify the data in accordance with the quality of the products available. Electronic

CLASSIFICATION AND PREDICTION OF VARIOUS CANCERS USING DATA MINING
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Abstract-Data mining is having great effect in the field of medical diagnosis and risk prediction of disease. Cancer is not just one disease but many diseases. There are more than 100 different type of cancer such as skin, oral, brain etc. Cancer affect the body cells In this paper, the mining classification rules for gene expression data of yeast S. Cerevisiae is carried out using enhanced quickreduct fuzzy-rough feature selection (EQRFR-FS) with ant colony optimisation (ACO). Rough sets theory deals with uncertainty and vagueness of

Imbalanced Classification in Predictive data mining using GSVM Algorithm
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Abstract-The paper addresses some theoretical and sensible aspects of information mining, specializing in prophetical data processing, wherever 2 central forms of prediction issues are discussed: classification and regression. additional accent is formed on prophetical

Effective Classification Technique Enhanced Using Genetic Algorithm: For Data MiningDisease in the Incumbents to the Health Centre
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Abstract: The diagnosis of disease is a vital and intricate job in the incumbents to the health centre. The proposed method combines the learning algorithm of BP neural network with genetic algorithm to train BP network and optimize the weight values of the network in a

EFFECTIVE DATA MINING FOR PROPER MINING CLASSIFICATION USING NEURAL NETWORKS
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ABSTRACT With the development of database, the data volume stored in database increases rapidly and in the large amounts of data much important information is hidden. If the information can be extracted from the database they will create a lot of profit for the
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data mining research papers 2012 section 4
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