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Data Mining: Concepts and Techniques

Формат:      Страниц 770
     твердый переплет
Jiawei H.    
Elsevier Urban & Partner    
4122 руб
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Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. Whether you are a seasoned professional or a new student of data mining, this book has much to offer you: * A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data. * Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning. * Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data — including stream data, sequence data, graph structured data, social network data, and multi-relational data. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. Our ability to generate and collect data has been increasing rapidly.
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Раздел: Наматрасники
Data Mining, Visual Mining, Text Mining, OLAP. Гриф УМО ВУЗов России (+ CD-ROM) Технологии анализа данных: Учебное пособие БХВ-Петербург Барсегян А.А.
Книга является вторым, обновленным и дополненным, изданием учебного пособия "Методы и модели анализа данных: OLAP и Data Mining".
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Data Mining and Computational Intelligence in Genomics. Methods for Gene Expression Data Analysis Книга по Требованию Andrei D.
Therefore, this book presents a series of computational methods and algorithms, capable of extracting valuable biological knowledge from this type of data.
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Algorithms for Frequent Itemset Mining and Database Sanitization. Data Mining Книга по Требованию Yu-Chiang L.
Chapter 2 introduces background work on data mining, share mining, utility mining, and privacy-preserving data mining.
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Managing Supermarket Customer Offers in a Wireless World. Using Data Mining with Mobile Applications Книга по Требованию Volker H.
These offers have been based on customer purchasing patterns which were found by analysing data that had been generated by the use of loyalty card schemes.
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Interactive Data Mining Книга по Требованию
Based on the conceptual framework, a prototype of Interactive Classification System (ICS) has been implemented.
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Causal Inferences and Abductive Reasoning. Between Automated Data Mining and Latent Constructs Книга по Требованию Chong H.Y.
Almost every statistics instructor emphasizes to their classes that a strong association does not necessarily imply causation.
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Biomedical Data Mining Using Machine Learning. An Experimental Account Книга по Требованию Ekaterina S.
More specifically we address the task of gene name disambiguation.
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Sequential and Time Series Data Mining New Methods for Mining Sequential and Time Series Data. Книга по Требованию Ghazi A.
It covers a variety of techniques aimed at discovering diverse types of patterns on the basis of the requirements of the domain.
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Evolutionary Data Mining Книга по Требованию Frederic P. M.
While it can be used for mining data from DNA sequences, it is not limited to biological contexts and can be used in any classification-based prediction scenario, which helps "predict the value . . . of a user-specified goal attribute based on the values of other attributes. " For instance, a banking institution might want to predict whether a customer' s credit would be "good" or "bad" based on their age, income and current savings. Evolutionary algorithms for data mining work by creating a series of random rules to be checked against a training dataset. The rules which most closely fit the data are selected and are mutated. The process is iterated many times and eventually, a rule will arise that approaches 100% similarity with the training data. This rule is then checked against a test dataset, which was previously invisible to the genetic algorithm. Evolutionary data mining, or genetic data mining is an umbrella term for any data mining using evolutionary algorithms. High Quality Content by WIKIPEDIA articles!
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Cross Industry Standard Process for Data Mining Книга по Требованию Lambert M. S.
In 1997 it got underway as a European Union project under the ESPRIT funding initiative.
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In the second chapter Sammon' s Mapping method is studied and improved. Sammon' s Mapping is a projection method which simulates the high-dimension space to a low- dimension one.
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Data Mining: Theories, Algorithms, and Examples Human Factors and Ergonomics Taylor and Francis
New technologies have enabled us to collect massive amounts of data in many fields.
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Handbook of Mining Details Книга по Требованию Journal M.
Несмотря на то, что была проведена серьезная работа по восстановлению первоначального качества издания, на некоторых страницах могут обнаружиться небольшие "огрехи": помарки, кляксы и т. п. Книга представляет собой репринтное издание.
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Text Mining to Support Business Intelligence. Analysing Business Data Книга по Требованию Haralampos K.
In most companies and organisations valuable time and effort is wasted in ineffective searches through multiple information sources including web sites and other conventional sources.
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Cambridge Mathematics Direct 3 Measures, Shape, Space and Handling Data Copymasters Cambridge University Press Jane C.
Cambridge Mathematics Direct is a structured set of maths resources for primary schools.
2057 руб
Cambridge Mathematics Direct 4 Measures, Shape, Space and Handling Data Pupil's Book Cambridge University Press Jane C.
They also show which activities require the teacher’s input. - incorporate a variety of activities including word problems, games, open-ended activities, pupil generated ideas - differentiated activities provided for average, least able and most able pupils - pages show where teacher input is required CMD 4 Measures, Shape, Space and Handling Data Textbook provides practice in key mathematical concepts and skills.
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Cambridge Mathematics Direct 5 Measures, Shape, Space and Handling Data Teacher's Book Cambridge University Press Sandy C.
The clearly structured lesson plans provide a manageable approach to differentiation and activities are included for children of all abilities.
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Data structures and Algorithms in Java John Wiley & Sons (Wiley) Goodrich M.T.
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Spatiotemporal Interpolation Methods in GIS. Exploring Data for Decision Making Книга по Требованию Lixin L.
Exploring large data sets with the aim of extracting useful information for decision making can be challenging.
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Computational Neural Models for Body Surface ECG Data Analysis. Body Surface Cardiac Mapping Книга по Требованию Jesus L.
Firstly, to develop a classification framework for an accurate and early diagnosis of acute MI. This decision support system encompasses computational neural models with the input space based on BSCM.
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