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Data Mining

knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains;

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Data Mining

knowledge from these data falls far behind our pace of collecting the data. Data Mining: Theories, Algorithms, and Examples introduces and explains;

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Data Mining Algorithms

Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for;

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Data Mining Concept Animation Library

Data mining is the automated extraction of hidden predictive information from large data sets. To study new algorithms or compare different;

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Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies;

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Data Mining and Applications in Genomics

Data Mining and Applications in Genomics contains the data mining algorithms and their applications in genomics, with frontier case studies;

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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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Introduction to Data Mining

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major;

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Contrast Data Mining

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and;

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Principles of Data Mining

The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics;

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Data Mining and Knowledge Discovery With Evolutionary Algorithms

This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become;

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Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data

Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning;

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Introduction to Data Mining, Global Edition

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept;

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Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories

This SpringerBrief provides an overview within data mining of spatiotemporal frequent pattern mining from evolving regions to the;

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Robust Data Mining

data mining techniques aim to create new algorithms resilient to error and noise. This work encapsulates all the latest applications of robust;

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The Top Ten Algorithms in Data Mining

Identifying some of the most influential algorithms that are widely used in the data mining community, this work provides a description;

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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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Randomized Algorithms in Automatic Control and Data Mining

In the fields of data mining and control, the huge amount of unstructured data and the presence of uncertainty in system descriptions have;

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Temporal Data Mining

Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business;

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Temporal Data Mining

Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business;

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Data Mining and Knowledge Discovery for Geoscientists

Currently there are major challenges in data mining applications in the geosciences. This is due primarily to the fact that there is a;

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5th International Symposium on Data Mining Applications

The 5th Symposium on Data Mining Applications (SDMA 2018) provides valuable opportunities for technical collaboration among data mining and;

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Advanced Data Mining and Applications

This book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held;

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Trends and Applications in Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining (PAKDD) held in Tainan, Taiwan, in May 2014. The 73 revised papers presented were carefully reviewed and;

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Advances in Knowledge Discovery and Data Mining

in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016. The 91 full papers were carefully reviewed;

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Advances in Knowledge Discovery and Data Mining

in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016. The 91 full papers were carefully reviewed;

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Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery

Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable;

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