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On the application of data mining algorithms for

1 天前  Data mining methods are often implemented at various sectors today for analyzing available data and extracting information and knowledge to support decision-making. Educational data mining is an emerging discipline, concerned with developing methods and algorithms that discover knowledge from data originating from educational environments. This paper study the application of data mining

5 Data mining applications Expert System Expert.ai

Data mining applications for Intelligence. Data mining helps analyze data and clearly identifies how to connect the dots among different data elements. This is an essential aspect for government agencies: Reveal hidden data related to money laundering, narcotics trafficking, corporate fraud, terrorism, etc.

The application of data mining techniques in financial

From analysing 49 journals, Ngai et al (2011), claimed insurance fraud as the most prominent area for application of data mining techniques, whereas security and commodity fraud is the most scarce

Mining Educational Data for Students' Placement

2014-8-19  In data mining, to predict the performance of student there are various data mining tools, where the work of the paper is to set the default parameter of various algorithms to gain the highest accuracy, which is hard for a non-technical person. In recent year, some works have done on automatic parameter tuning.

Application of data mining in a maintenance system for

2020-7-15  about the implementation of data mining algo-rithms on an F-18 aircraft data as well as meth-ods for properly structuring a database system to store this data. They develop data mining mod-els for detection of problems before they become critical. Liao et al. 2012 present a work were a novel data-driven machinery prognostic approach

ApplicAtion of DAtA Mining in Agriculture

2015-8-21  26 ApplicAtion of DAtA Mining in Agriculture B. MiloviC1 and v.RadojeviC2 1 Agricultural Enterprise “Sava Kovačevic” at Vrbas, 21460 Vrbas, Serbia 2 University of Novi Sad, Faculty of Agriculture, 21000 Novi Sad, Serbia Abstract MiloviC, B. and v. RadojeviC, 2015. application of data mining in agriculture.

Application of data mining and intelligent agent

2012-5-2  on the application of data mining (DM) techniques on possible available datasets. This methodology devel-oped within AA, results in the extraction of agent knowledge in the form of a decision model (e.g. a decision tree). The extracted knowledge is expressed in Predictive Modelling Markup Language (PMML) (Data Mining Group 2001) documents and

Application of data mining in telecommunication industry

used to achieve this. Data tier stores data for the application and MySQL was used to query the database. Data mining approach involves the application of data mining model on the sales data in order to carry out analysis. Database design, input, output This

An application of data mining to fruit and vegetable

2012-7-25  G. Holmes et al. / An application of data mining for fruit and vegetable sample identification using GC-MS 2.2 Chromatograms A GC-MS instrument produces data for a sample termed a chromatogram. This is essentially a succession of ion abundance counts produced by the mass spectrometer. Figure 2 depicts a potato sample.

A global-scale data set of mining areas Scientific Data

2020-9-8  Grid data derived from the polygons is available at 30 arcsecond, 5 arcminute, and 30 arcminute spatial resolution, providing a ready-to-use data set for modeling purposes with the mining

Educational Data Mining Applications and Trends

This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as

Data mining application to healthcare fraud detection:

2020-7-14  The healthcare sector is an interesting target for fraudsters. The availability of a great amount of data makes it possible to tackle this issue with the adoption of data mining techniques, making the auditing process more efficient and effective. This research has the objective of developing a novel data mining model devoted to fraud detection among hospitals using Hospital Discharge Charts

Data Mining Techniques for Anti Money Laundering

2017-11-7  application of data mining. The aim of this study was to review research conducted in the field of fraud detection with (Kirkos et al, 2007). Applying data mining to fraud detection as part of a routine financial audit can be challenging and, as we will explain, data mining should be used when the potential payoff is high.

Predictive Data Mining for Medical Diagnosis: An

2011-3-30  The successful application of data mining in highly visible fields like e-business, marketing and retail has led to its application in other industries and sectors. Among these sectors just discovering is healthcare. The healthcare environment is still „information rich‟ but „knowledge poor‟. There is a wealth of data available

ApplicAtion of DAtA Mining in Agriculture

2015-8-21  26 ApplicAtion of DAtA Mining in Agriculture B. MiloviC1 and v.RadojeviC2 1 Agricultural Enterprise “Sava Kovačevic” at Vrbas, 21460 Vrbas, Serbia 2 University of Novi Sad, Faculty of Agriculture, 21000 Novi Sad, Serbia Abstract MiloviC, B. and v. RadojeviC, 2015. application of data mining in agriculture.

Application of data mining in a maintenance system for

2020-7-15  about the implementation of data mining algo-rithms on an F-18 aircraft data as well as meth-ods for properly structuring a database system to store this data. They develop data mining mod-els for detection of problems before they become critical. Liao et al. 2012 present a work were a novel data-driven machinery prognostic approach

Application of data mining and intelligent agent

2012-5-2  on the application of data mining (DM) techniques on possible available datasets. This methodology devel-oped within AA, results in the extraction of agent knowledge in the form of a decision model (e.g. a decision tree). The extracted knowledge is expressed in Predictive Modelling Markup Language (PMML) (Data Mining Group 2001) documents and

Application of data mining in telecommunication industry

used to achieve this. Data tier stores data for the application and MySQL was used to query the database. Data mining approach involves the application of data mining model on the sales data in order to carry out analysis. Database design, input, output This

PREDICTING DROPOUT STUDENT: AN APPLICATION OF

2017-4-13  understandable patterns in data (Fayyad et al., 1996). The use of data mining in education has grown in recent years for several reasons: a considerable increase in the amount of data, technological advances in computer sciences, and well-developed of tools for analyses (Barker & Siemens, in press). Data mining includes several types of tasks.

Data Mining for Business Analytics: Concepts,

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text

Trajectory data mining: A review of methods and

2020-10-13  2.2 Trajectory data mining Data mining is an important step of a process, commonly known as knowledge discov-ery [37, 95] that extracts useful information from huge datasets. Data mining methods and applications have been widely surveyed in the general data mining domain. For in-stance, a survey of data mining methods for classical relational

Data Mining Techniques for Anti Money Laundering

2017-11-7  application of data mining. The aim of this study was to review research conducted in the field of fraud detection with (Kirkos et al, 2007). Applying data mining to fraud detection as part of a routine financial audit can be challenging and, as we will explain, data mining should be used when the potential payoff is high.

An application of data mining to fruit and vegetable

2012-7-25  G. Holmes et al. / An application of data mining for fruit and vegetable sample identification using GC-MS 2.2 Chromatograms A GC-MS instrument produces data for a sample termed a chromatogram. This is essentially a succession of ion abundance counts produced by the mass spectrometer. Figure 2 depicts a potato sample.

Predictive Data Mining for Medical Diagnosis: An

2011-3-30  The successful application of data mining in highly visible fields like e-business, marketing and retail has led to its application in other industries and sectors. Among these sectors just discovering is healthcare. The healthcare environment is still „information rich‟ but „knowledge poor‟. There is a wealth of data available