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142 results for "data mining"
MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS By DR. SUBHENDU KUMAR PANI
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Web Mining is an important sub-branch of Data Mining. Data mining is defined as a technique of finding hidden information in a database [1]. It may be called as data driven discovery, explorative... More > data analysis, deductive learning. Web mining is mining of data related to the World Wide Web [2]. This may be data actually present in Web pages or data related to the Web activity.< Less
ASSESSMENT OF WATER QUALITY USING DATA MINING TECHNIQUES By Dr. Kamakshaiah Kolli
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Data Mining is the procedure of dissecting Data from alternate points of view and compressing it into helpful data keeping in mind the end goal to build income, basic leadership capacities and to... More > diminish cost. It examinations Data in various measurements and distinguishes the relationship among Data. To start with, we should know the distinction amongst Data. Data is a truth, number or content that can be prepared by a PC. Associations create tremendous measure of Data in various organizations and store them in various databases. Data can be named as follows: Operational Data – Sales, Purchase, book keeping and stock Non Operational Data – Forecast Data Meta Data – Data about Data.< Less
DATA.MINE CONFLUX - EXHIBITION CATALOGUE By O Fluxo Editions
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The “Data.Mine Conflux” Catalogue offers an extended insight of each artwork presented at the online exhibition at http://neverlandspace.com/exhibition/datamine-conflux It also features... More > some additional content like research images, an extra essay from Krystal South on how to ‘Identify Yrself’ in the www, an art related astrological forecast by Lauren Reid and Perla Montelongo, a proposal for moving Kiruna based on increasing mining activity by the urban unplanning studio Scapeous, some visual material by Kate Malykh, Etienne Garachon, Jacob Broms Engblom and many more. View some inside pages here: http://www.ofluxo.net/data-mine-conflux-o-fluxos-online-exhibition-2/< Less
KB Neural Data Mining: with Python sources By Roberto Bello
eBook (PDF): $0.00
The aim of this work is to present and describe in detail the algorithms to extract the knowledge hidden inside data using Python language, which allows us to read and easily understand the nature... More > and the characteristics of the rules of the computing utilized, as opposed to what happens in commercial applications, which are available only in the form of running codes, which remain impossible to modify. The algorithms of computing contained within the work, are minutely described, documented and available in the Python source format, and serve to extract the hidden knowledge within the data whether they are textual or numerical kinds. There are also various examples of usage, underlining the characteristics, method of execution and providing comments on the obtained results.< Less
Intruduction to Statistical Tools Used for Data Mining By Jim Rutledge, Ph.D.
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Data Vision Version
Introduction to Statistical Tools Used for Data Mining By Jim Rutledge, Ph.D.
eBook (PDF): $0.00
Many projects can be very data intensive and the statistical tools taught in traditional college curricula are often inadequate for solving the problem at hand. While there are many aspects and... More > definitions of data mining, the basic idea is to find patterns in data sets. Although marketed for large databases, the techniques are applicable to any size data set. While data management is an important subject, this course will focus on the statistical models used in data mining. It will cover the most useful tools such as linear regression, logistic regression, classification trees, discriminate analysis, neural networks, clustering, nearest neighbors, bump hunting, and market basket analysis. While these data mining tools may sound exotic and difficult to understand, they are actually fairly straightforward and modern software makes it easy to use them. This is a color version for AAA.< Less
Advanced Analysis and Data Mining By Mustafa Ebaid
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This Advanced Analysis and Data Mining book meets the needs of professional analysts, scientists, researchers specialists readers and university and graduate students and all those interested in... More > scientific research, data analysis and data mining in the fields of humanities and various applied sciences, also it meets the needs of professional analysts and in the departments of statistics, information, marketing and analysis, risk management and research community, development, planning and decision support, small and medium enterprises holders and directors of strategic senior management in institutions and companies specialized in all areas.< Less
Data as Capta By Johanna Drucker
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As humanists adopt the methods of empirical sciences to produce visualizations in digital data mining, the question of whether the foundations of humanistic interpretation are served by such... More > approaches arises. This project poses a critique of the concept of data, suggests an alternative concept, capta, and then explores some systematic means of creating visualizations rooted in humanistic approaches.< Less
Data Mining Study 2010: Field Test & Benchmarking - PRINT By Peter Neckel et al.
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The mayato Data Mining Study 2010 uses a large number of test data records (1.8 million rows) to compare five data mining tools and suites: SAS Enterprise Miner 6.1, STATISTICA Data Miner 9.0 from... More > StatSoft, KNIME 2.0.3, KXEN Analytic Framework 5.1.1, and SAP NetWeaver 7.0 Data Mining Workbench. This year’s study focuses on investigating cross-selling and up-selling potential. Using a case study, the entire data mining process is undergone in a comprehensive test procedure – from data preparation and data exploration to the (graphical) display and interpretation of the results. Factors that were assessed include ease of use, features, system response with large data quantities, and stability. Furthermore, the execution speed with many different parameter settings was measured and documented. More information can be found on our website (www.mayato.com). Students and Universities can purchase the Study for €99 by sending an email with a qualifying document to sales@mayato.com< Less
Data Mining Study 2010: Field Test & Benchmarking - PDF By Peter Neckel et al.
eBook (PDF): $374.92
The mayato Data Mining Study 2010 uses a large number of test data records (1.8 million rows) to compare five data mining tools and suites: SAS Enterprise Miner 6.1, STATISTICA Data Miner 9.0 from... More > StatSoft, KNIME 2.0.3, KXEN Analytic Framework 5.1.1, and SAP NetWeaver 7.0 Data Mining Workbench. This year’s study focuses on investigating cross-selling and up-selling potential. Using a case study, the entire data mining process is undergone in a comprehensive test procedure – from data preparation and data exploration to the (graphical) display and interpretation of the results. Factors that were assessed include ease of use, features, system response with large data quantities, and stability. Furthermore, the execution speed with many different parameter settings was measured and documented. More information can be found on our website (www.mayato.com). Students and Universities can purchase the Study for €99 by sending an email with a qualifying document to sales@mayato.com< Less

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