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  • Predicting Student Performance Using Advanced Learning

    Predicting Student Performance using Advanced Learning Analytics . Ali Daud. a,d a . Faculty of Computing and Information Technology, King Abdulaziz University.

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  • Benfords Law Data Mining And Financial Medicaid Data

    Benford’s Law, data mining, and financial fraud: a case study in New York State Medicaid data B. Little1, R. Rejesus2, M. Schucking3 & R. Harris4.

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  • Last Level Cache (LLC) Performance Of Data Mining

    Abstract With the continuing growth in the amount of genetic data, members of the bioinformatics community are d eveloping a variety of data-mining.

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  • 6. Dicretization Methods 6.1 The Purpose Of Discretization

    Information, or data mining algorithms that assume discrete values. 230. The goal of discretization is to reduce the number of values a continuous variable assumes by grouping them into a number, b, of intervals or bins. Two key problems in association with discretization are how to select the number of intervals or bins and how to decide on their width. Discretization can be performed with or.

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  • Application Of Data Mining Classification In Employee

    Performance is strong. Data Mining can be used for knowledge discovery of interest in Human Resources Management (HRM). We used the Data Mining classification technique for the extraction of knowledge significant for predicting employee performance using previous appraisal records a public management development institute in Kenya. The Cross Industry Standard Process for Data Mining.

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  • Chapter 5 Performance Evaluation Of The Data Mining Models

    71 Perfomance comparison of data mining models In the table 5.1, a confusion matrix is shown, for which, the various values and related equations are described.

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  • Employee Motivation And Work Performance: A Comparative

    Findings: The study observed that, due to the risk factors associated with the mining industry, management has to ensure that employees are well motivated to curb the rate at which employees embark on industrial unrest which affect performance, and employees are to comply.

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  • Using Machine Learning Algorithms For Breast Cancer

    Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis Classification and data mining methods are an effective way to classify data. Especially in medical field, where those methods are widely used in diagnosis and analysis to make decisions. In this paper, a performance comparison between different machine learning algorithms: Support Vector Machine (SVM.

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  • Expert Systems With Applications ISI Articles

    The objective of the current study is to apply a data mining technique to enhance tax evasion detection performance. Using a data mining technique, a screening framework is developed to.

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  • MAFIA: A Performance Study Of Mining Maximal Frequent Itemsets

    MAFIA assumes that the entire database (and all data structures used for the algorithm) completely ?t into main memory. Since all algorithms for ?nding association rules, including algorithms that work with disk-resident databases, are CPU-bound, we believe that our study sheds light on some important performancebottlenecks.

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  • A Study Of Improving The Performance Of Mining

    Read "A Study of Improving the Performance of Mining Multi-Valued and Multi-Labeled Data, Informatica" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips.

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  • High Performance Data Mining In Time Series: Techniques

    High Performance Data Mining in Time Series: Techniques and Case Studies by Yunyue Zhu A dissertation submitted in partial ful?llment of the requirements for the degree of.

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  • A Study On Prediction Performance Of Some Data Mining

    Data mining algorithms create how the cases for a data mining model are calculate. Data mining illustration algorithms present the decision-making capabilities necessary to categorize, segment.

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  • Information Security In Big Data: Privacy And Data Mining

    Abstract: The growing popularity and development of data mining technologies bring serious threat to the security of individual,'s sensitive information.

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  • MAFIA: A Performance Study Of Mining Maximal Frequent Itemsets

    MAFIA: A Performance Study of Mining Maximal Frequent Itemsets Doug Burdick University of Wisconsin-Madison who0ps99 Manuel Calimlim.

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  • The Theory And Practice Of Secure Data Mining | Data

    15.07.2019 · A third approach (fig. 3) allows the consumer to first provide the data owner with the "method" of mining in the form of a mining object, to which the owner will subject the data.

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  • Performance Evaluation Of Data Mining Techniques

    Abstract. Data mining has gained immense popularity in various fields of medical, education and industry as well. Data mining is a process of predicting the result and extraction of.

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  • Applying Data Mining Techniques To Improve Information

    This was achieved through techniques of data mining, with specific reference to a single cache system. 3. Objectives. The objectives are as follows: (i) Identify various security threats in cloud computing. (ii) Enhance the security of the cloud through data mining techniques by making use of.

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  • Empirical Study On Applications Of Data Mining Techniques

    In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data.

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  • Data Mining: A Prediction For Performance Improvement

    Data Mining can be used in educational field to enhance our understanding of learning process to focus on identifying, extracting and evaluating variables related to the learning process of students as described by Alaa el-Halees [2]. Mining in educational environment is called Educational Data Mining.

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  • A Study Of Efficiency And Accuracy Of Secure Multiparty

    An analysis of the accuracy and efficiency of multiparty secured protocols is carried out so that both measures can be optimally exploited in the design of.

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  • A Performance Study Of Data Mining Techniques: Multiple

    The purpose of this study is to compare the performance of two data mining techniques viz., factor analysis and multiple linear regression for different sample sizes on three unique sets of data.

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