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Domain Driven Data Mining

outputs. This monograph, Domain Driven Data Mining, is motivated by the real-world challenges to and complexities of the current KDD methodologies;

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Proactive Data Mining with Decision Trees

This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only;

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Computational Medicine in Data Mining and Modeling

further the knowledge in the medical domain. The authors focus on applying data mining to the medical domain, including mining the sets;

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Decision Trees for Business Intelligence and Data Mining

This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business;

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Rough Sets and Knowledge Technology

, applications of rough sets, intelligent systems and applications, knowledge technology, domain-oriented data-driven data mining, uncertainty;

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Mining Data for Financial Applications

This book constitutes revised selected papers from the 4th Workshop on Mining Data for Financial Applications, MIDAS 2019, held;

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Event Mining

Event mining encompasses techniques for automatically and efficiently extracting valuable knowledge from historical event/log data. The;

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Intelligent Knowledge

This book is mainly about an innovative and fundamental method called intelligent knowledge to bridge the gap between data mining and;

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Event Mining for Explanatory Modeling

This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used;

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Event Mining for Explanatory Modeling

This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used;

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Recent Advances on Soft Computing and Data Mining

the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to;

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Advances in Knowledge Discovery and Data Mining

learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors;

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Advances in Knowledge Discovery and Data Mining

learning and embedding; mining behavioral data; deep learning; feature extraction and selection; human, domain, organizational and social factors;

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Managing and Mining Graph Data

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety;

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Managing and Mining Graph Data

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety;

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Mastering Data Mining with Python - Find patterns hidden in your data

Learn how to create more powerful data mining applications with this comprehensive Python guide to advance data analytics techniques;

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Association Rule Hiding for Data Mining

been solely investigated by a new research domain, the so-called privacy preserving data mining. Association rule hiding is a new technique;

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Data Fusion and Data Mining for Power System Monitoring

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining;

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Data Fusion and Data Mining for Power System Monitoring

Data Fusion and Data Mining for Power System Monitoring provides a comprehensive treatment of advanced data fusion and data mining;

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Introduction to Data Mining for the Life Sciences

. Traditionally, techniques such as kernel learning methods, pattern recognition, and data mining, have been the domain of researchers in areas such as;

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Data Mining for Systems Biology

This fully updated book collects numerous data mining techniques, reflecting the acceleration and diversity of the development of data;

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Data-Driven Mining, Learning and Analytics for Secured Smart Cities

This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies;

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Exploratory Data Mining and Data Cleaning

* Written for practitioners of data mining, data cleaning and database management. * Presents a technical treatment of data quality;

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Data Mining

, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce;

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Data Mining

, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce;

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AdaBoost Extensions for Cost-Sensitive Classification

This book provides a review and a research of a special type of classification technique which is known as cost-sensitive data mining. Cost;

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Data Mining for Social Network Data

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved;

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