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共24筆商品，1/2頁
Classification and Data Mining
1.

Classification and Data Mining

作者：Antonio Giusti (EDT); Gunter Ritter (EDT); Maurizio Vichi (EDT)  出版社：Springer Verlag  出版日：2012/10/31 裝訂：平裝
?????????This volume contains both methodological papers showing new original methods, and papers on applications illustrating how new domain-specific knowledge can be made available from data by clev
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Data Mining ─ Foundations and Intelligent Paradigms, Clustering, Association and Classification
2.

Data Mining ─ Foundations and Intelligent Paradigms, Clustering, Association and Classification

作者：Dawn E. Holmes (EDT); Lakhmi C Jain (EDT)  出版社：Springer-Verlag New York Inc  出版日：2011/11/11 裝訂：精裝
There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Assoc
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Fundamentals of Image Data Mining ― Analysis, Features, Classification and Retrieval
90折
3.

Fundamentals of Image Data Mining ― Analysis, Features, Classification and Retrieval

作者：Dengsheng Zhang  出版社：Springer-Verlag New York Inc  出版日：2019/05/24 裝訂：精裝
This reader-friendly textbook presents a comprehensive review of the essentials of image data mining, and the latest cutting-edge techniques used in the field. The coverage spans all aspects of image
無庫存，下單後進貨(到貨天數約45天)
定價：3119 元， 優惠價：9 2807
Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval
4.

Fundamentals of Image Data Mining: Analysis, Features, Classification and Retrieval

作者：Dengsheng Zhang  出版社：Springer Nature  出版日：2021/05/13 裝訂：精裝
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Classification Functions for Machine Learning and Data Mining
5.

Classification Functions for Machine Learning and Data Mining

作者：Tsutomu Sasao  出版社：Springer Nature  出版日：2024/07/15 裝訂：平裝
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Classification Functions for Machine Learning and Data Mining
滿額折
6.

Classification Functions for Machine Learning and Data Mining

作者：Tsutomu Sasao  出版社：Springer Nature  出版日：2023/08/04 裝訂：精裝
無庫存，下單後進貨(到貨天數約30-45天)
定價：3189 元， 優惠價：1 3189
Data Classification and Incremental Clustering in Data Mining and Machine Learning
7.

Data Classification and Incremental Clustering in Data Mining and Machine Learning

作者：Sanjay Chakraborty  出版社：Springer Nature  出版日：2023/05/25 裝訂：平裝
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Data Classification and Incremental Clustering in Data Mining and Machine Learning
8.

Data Classification and Incremental Clustering in Data Mining and Machine Learning

作者：Sanjay Chakraborty  出版社：Springer Nature  出版日：2022/06/11 裝訂：精裝
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Data Mining and Data Warehousing ― Principles and Practical Techniques
9.

Data Mining and Data Warehousing ― Principles and Practical Techniques

作者：Parteek Bhatia  出版社：Cambridge Univ Pr  出版日：2019/02/28 裝訂：平裝
Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are
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Classification And Modeling With Linguistic Information Granules ─ Advanced Approaches To Linguistic Data Mining
10.

Classification And Modeling With Linguistic Information Granules ─ Advanced Approaches To Linguistic Data Mining

作者：Hisao Ishibuchi; Tomoharu Nakashima; Manabu Nii  出版社：Springer-Verlag New York Inc  出版日：2004/10/16 裝訂：精裝
Whereas computer systems can easily handle even complicated and nonlinear mathematical models, human information processing is mainly based on linguistic knowledge. So the main advantage of using ling
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Proactive Data Mining With Decision Trees
11.

Proactive Data Mining With Decision Trees

作者：Haim Dahan; Shahar Cohen; Lior Rokach; Oded Maimon  出版社：Springer Verlag  出版日：2014/03/31 裝訂：平裝
This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but al
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定價：2750 元， 優惠價：1 2750
Data Mining and Machine Learning ― Fundamental Concepts and Algorithms
90折
12.

Data Mining and Machine Learning ― Fundamental Concepts and Algorithms

作者：Mohammed J. Zaki  出版社：Cambridge Univ Pr  出版日：2020/02/29 裝訂：精裝
The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.
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定價：3653 元， 優惠價：9 3288
DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: NAIVE BAYES, NEAREST NEIGHBORS and NEURAL NETWORKS: Examples with MATLAB
滿額折
13.

DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: NAIVE BAYES, NEAREST NEIGHBORS and NEURAL NETWORKS: Examples with MATLAB

作者：César Pérez López  出版社：LULU PR  出版日：2021/11/15 裝訂：平裝
無庫存，下單後進貨(到貨天數約30-45天)
定價：1649 元， 優惠價：1 1649
DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: SUPPORT VECTOR MACHINE, LOGISTIC REGRESSION, DISCRIMINANT ANALYSIS and DECISIO
滿額折
14.

DATA MINING and MACHINE LEARNING. CLASSIFICATION PREDICTIVE TECHNIQUES: SUPPORT VECTOR MACHINE, LOGISTIC REGRESSION, DISCRIMINANT ANALYSIS and DECISIO

作者：César Pérez López  出版社：LULU PR  出版日：2021/11/12 裝訂：平裝
無庫存，下單後進貨(到貨天數約30-45天)
定價：1649 元， 優惠價：1 1649
Learning Data Mining with Python: Use Python to manipulate data and build predictive models, 2nd Edition
滿額折
15.

Learning Data Mining with Python: Use Python to manipulate data and build predictive models, 2nd Edition

作者：Robert Layton  出版社：Packt Pub Ltd  出版日：2017/04/27 裝訂：平裝
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries
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定價：1786 元， 優惠價：79 1411
Survey of Text Mining II: Clustering, Classification, and Retrieval
16.

Survey of Text Mining II: Clustering, Classification, and Retrieval

作者：Michael W. Berry (EDT); Malu Castellanos (EDT)  出版社：Springer-Verlag New York Inc  出版日：2007/11/30 裝訂：精裝
The proliferation of digital computing devices and their use in communication has resulted in an increased demand for systems and algorithms capable of mining textual data. Thus, the development of t
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Algorithms from and for Nature and Life ― Classification and Data Analysis
17.

Algorithms from and for Nature and Life ― Classification and Data Analysis

作者：Berthold Lausen (EDT); Dirk Van Den Poel (EDT); Alfred Ultsch (EDT)  出版社：Springer-Verlag New York Inc  出版日：2013/04/30 裝訂：平裝
This volume provides approaches and solutions to challenges occurring at the interface of research fields such as, e.g., data analysis, data mining and knowledge discovery, computer science, operation
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Modern Technologies for Big Data Classification and Clustering
18.

Modern Technologies for Big Data Classification and Clustering

作者：Hari Seetha (EDT); M. Narasimha Murty (EDT); B. K. Tripathy (EDT)  出版社：Information Science Reference  出版日：2017/08/31 裝訂：精裝
Focusing on classifying and clustering techniques, computer scientists look at the multidisciplinary nature of big data and its applications and challenges in various fields. Their topics include
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Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning
19.

Modern Multivariate Statistical Techniques: Regression, Classification, and Manifold Learning

作者：Alan Julian Izenman  出版社：Springer Verlag  出版日：2008/07/07 裝訂：精裝
Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the
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Data Classification ─ Algorithms and Applications
20.

Data Classification ─ Algorithms and Applications

作者：Charu C. Aggarwal (EDT)  出版社：Taylor & Francis  出版日：2014/07/25 裝訂：精裝
Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine
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