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An Efficient Mechanism for Data Mining Based On Item Sets Features

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Data Fusion and Data Mining for Power System Monitoring

techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and;

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Data Fusion and Data Mining for Power System Monitoring

techniques for power system monitoring with focus on use of synchronized phasor networks. Relevant statistical data mining techniques are given, and;

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Feature Selection in Data Mining - Approaches Based on Information Theory

set of features will almost certainly overfit on future data sets. The book presents streamwise feature selection which interleaves the;

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Data Mining with SPSS Modeler

resampling techniques as well as an extensive case study on the cross-industry standard process for data mining.;

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Transactions on Rough Sets XIII

contains regular articles on mining temporal software metrics data, C-GAME discretization method, perceptual tolerance intersection as an example;

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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization;

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Association Rule Hiding for Data Mining

in data mining, which studies the problem of hiding sensitive association rules from within the data. Association Rule Hiding for Data Mining;

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Data Mining & Predictive Analytics

provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to;

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Data Mining Methods for Knowledge Discovery

Data Mining Methods for Knowledge Discovery provides an introduction to the data mining methods that are frequently used in the process;

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Image Mining

. The process of discovering valuable information from image data termed image mining finds its sources in data mining, content-based image;

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Data Mining for Business Intelligence

solutions. Data Mining for Business Intelligence, Second Edition is an excellent book for courses on data mining, forecasting, and decision support;

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Uncertainty Modeling for Data Mining

, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for;

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Data Mining

, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors;

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Neural Information Processing Part I

; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological;

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Neural Information Processing Part II

; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological;

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Neural Information Processing Part III

; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological;

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Neural Information Processing Part IV

; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological;

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Networks, Data Mining and Artificial Intelligence: Trends and Future Directions

significant contributions on design of efficient clustering algorithms for categorical and mixed data types. This section includes an exhaustive;

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Data Mining for Bioinformatics Applications

Data Mining for Bioinformatics Applications provides valuable information on the data mining methods have been widely used for solving;

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Bayesian Item Response Modeling

motives for writing this book is to give an introduction to the Bayesian methodology for modeling and analyzing item response data. A Bayesian;

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Machine Intelligence: Recent Advances

preserving data mining, as well as an authentication mechanism using fingerprint classification. Section V contains an extension of open source iCub;

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Python Data Mining Quick Start Guide

classification techniques. By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle. What you;

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Cube Based Incremental Data Mining

This work presents a cube-based approach for incremental data mining that operates on the data, rather than on the data mining algorithms;

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Foundations of Computational Intelligence 06

Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It;

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Lecture Notes In Data Mining

The continual explosion of information technology and the need for better data collection and management methods has made data mining an;

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Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and;

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