chapman hall crc data mining and knowledge

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2024年（1）

2022~2023 （1）

2020~2021 （6）

2018~2019 （5）

2016~2017 （12）

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平裝（12）

精裝（34）

作者

Arvind Kumar (Kent State University Bansal Department of Computer Science Ohio USA),Javed Iqbal (Kent State University Khan Computer Science Ohio USA),S. Kaisar (Improlabs LLC Alam Dayton New Jersey U （2）

Brian D. Bissett （2）

Chandan K. Reddy (EDT)/ Charu C. Aggarwal (EDT) （2）

Jesus (Imperial College London Rogel-Salazar UK) （2）

Jesus Rogel-salazar （2）

出版社/品牌

Taylor & Francis （15）

Chapman & Hall （14）

PBKTYFRL （5）

CRC Pr I Llc （4）

Productivity Press （4）

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共46筆商品，1/3頁

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1.Data Science and Analytics With Python

作者：Jesus Rogel-salazar 出版社：Chapman & Hall 出版日：2017/05/16 裝訂：精裝

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main conce

定價：6900 元，優惠價：9 6210

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2.Data Science and Machine Learning for Non-Programmers：Using SAS Enterprise Miner

作者：Dothang Truong 出版社：PBKTYFRL 出版日：2024/02/23 裝訂：精裝

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3.Data Mining With R—Learning by Case Studies

作者：Luis Torgo 出版社：Taylor & Francis 出版日：2010/11/09 裝訂：精裝

The versatile capabilities and large set of add-on packages make R an excellent alternative to many existing and often expensive data mining tools. Exploring this area from the perspective of a practi

定價：3358 元，優惠價：9 3022

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4.Rapidminer ─ Data Mining Use Cases and Business Analytics Applications

作者：Markus Hofmann (EDT); Ralf Klinkenberg (EDT) 出版社：Chapman & Hall 出版日：2017/04/15 裝訂：精裝

Written by leaders in the data mining community, including the developers of the RapidMiner software, this book provides an in-depth introduction to the application of data mining and business analyti

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5.Advances in Machine Learning and Data Mining for Astronomy

作者：Michael J. Way (EDT); Jeffrey D. Scargle (EDT); Kamal M. Ali (EDT); Ashok N. Srivastava (EDT) 出版社：Chapman & Hall 出版日：2016/10/31 裝訂：平裝

Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of stat

定價：3177 元，優惠價：9 2859

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6.Social Networks With Rich Edge Semantics

作者：Quan Zheng; David Skillicorn 出版社：CRC Pr I Llc 出版日：2017/09/30 裝訂：精裝

Social Networks with Rich Edge Semantics introduces a new mechanism for representing social networks in which pairwise relationships can be drawn from a range of realistic possibilities, including dif

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7.Mobility Data Modeling and Analysis

作者：Jalel Akaichi 出版社：Productivity Press 出版日：2016/12/06 裝訂：精裝

Nowadays, pervasive technologies are characterized by their ability to process data related to moving objects. This has resulted in a new data source type called Trajectory Data (TD) which is generate

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8.Data Clustering in C++: An Object-oriented Approach

作者：Guojun Gan 出版社：Chapman & Hall 出版日：2011/03/21 裝訂：精裝

Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different gr

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9.Computational Business Analytics

作者：Subrata Das 出版社：Taylor & Francis 出版日：2013/06/15 裝訂：精裝

Traditional business analytics have so far focused mostly on descriptive analyses of historical data using a myriad of sound statistical techniques. This book describes how numerical statistical techn

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10.Handbook of Educational Data Mining

作者：Cristobal Romero (EDT); Sebastian Ventura (EDT); Mykola Pechenizkiy (EDT); Ryan S. J. D. Baker (EDT) 出版社：CRC Press UK 出版日：2010/10/26 裝訂：平裝

Handbook of Educational Data Mining (EDM) provides a thorough overview of the current state of knowledge in this area. The first part of the book includes nine surveys and tutorials on the principal d

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11.Knowledge Discovery from Data Streams

作者：Joao Gama 出版社：Taylor & Francis 出版日：2010/05/25 裝訂：精裝

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of le

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12.Practical Graph Mining With R

作者：Nagiza F. Samatova (EDT) 出版社：Taylor & Francis 出版日：2013/03/26 裝訂：精裝

"Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It cover

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13.Music Data Mining

作者：Tao Li (EDT); Mitsunori Ogihara (EDT); George Tzanetakis (EDT) 出版社：CRC Press UK 出版日：2011/07/12 裝訂：精裝

The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles

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14.Advances in Machine Learning and Data Mining for Astronomy

作者：Kamal Ali (EDT); Ashok Srivastava (EDT); Michael J. Way (EDT); Jeffrey D. Scargle (EDT) 出版社：Chapman & Hall 出版日：2012/04/04 裝訂：精裝

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15.Introduction to Privacy-Preserving Data Publishing:Concepts and Techniques

作者：Benjamin C. M. Fung; Ke Wang; Ada Wai-chee Fu; Philip S. Yu 出版社：Chapman & Hall 出版日：2010/08/02 裝訂：平裝

Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to thi

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16.Large-Scale Machine Learning in the Earth Sciences

作者：Ashok N. Srivastava (EDT); Ramakrishna Nemani (EDT); Karsten Steinhaeuser (EDT) 出版社：Chapman & Hall 出版日：2017/06/30 裝訂：精裝

Large-scale machine learning, currently focused on the internet and/or social network analysis, could prove highly beneficial in the study of earth science, a broad multidisciplinary field of study th

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17.Support Vector Machines

作者：Yinjie Tian; Naiyang Deng; Chunhua Zhang 出版社：Taylor & Francis 出版日：2012/12/27 裝訂：精裝

"Preface Support vector machines (SVMs), which were introduced by Vapnik in the early 1990s, are proved effective and promising techniques for data mining. SVMs have recently been breakthroughs in adv

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18.Service-Oriented Distributed Knowledge Discovery

作者：Domenico Talia; Paolo Trunfio 出版社：Taylor & Francis 出版日：2012/10/16 裝訂：精裝

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and mach

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19.Computational Intelligent Data Analysis for Sustainable Development

作者：Ting Yu; Nitesh Chawla (EDT); Simeon Simoff (EDT) 出版社：Taylor & Francis 出版日：2013/04/02 裝訂：精裝

Intelligent data analysis techniques offer powerful solutions to collecting and analyzing vast quantities of environmental and economic data, which lead to better decision making for sustainable devel

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20.Text Mining and Visualization ─ Case Studies Using Open-Source Tools

作者：Markus Hofmann; Andrew Chisholm 出版社：Taylor & Francis 出版日：2016/01/04 裝訂：精裝

This introductory book for text and web mining utilizes only open source tools to illustrate and teach unique use case applications. Each use case consists of a fully implemented application based on

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