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Java Data Mining: Strategy, Standard, and Practice

in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining;

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A Practical Guide to Data Structures and Algorithms using Java

Data Structures and Algorithms using Java presents comprehensive coverage of fundamental data structures and algorithms in a unifying framework;

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Data Mining with SPSS Modeler

Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and;

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An Introduction to Data Structures, Algorithms and Java

Assuming fundamental programming skills in Java, Introduction to Data Structures and Algorithms with Java begins by introducing the concept;

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Java 13 Revealed

of your code and time-based release versioning of the Java platform to understand the Java release strategy. This book provides extensive coverage;

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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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Java 13 Revealed

of your code and time-based release versioning of the Java platform to understand the Java release strategy. This book provides extensive coverage;

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Java Persistence Hibernate

most popular provider of the Java Persistence standard, offers automatic and transparent object/relational mapping, making it a snap to work;

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Java I/O 2e

All of Java's Input/Output (I/O) facilities are based on streams, which provide simple ways to read and write data of different types. Java;

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Text Mining

This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections;

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Practical Graph Mining with R

Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a do-it-yourself approach;

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Mastering Java Machine Learning

already working in related areas: ideally, intermediate-level data analysts and data scientists with experience in Java. Preferably, you will have;

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Web Data Mining

This book provides a comprehensive text on Web data mining. Key topics of structure mining, content mining, and usage mining are covered;

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Java

language, including GUIs, applets, input/output, and elementary data structures, enabling students to use a wide variety of tools when writing Java;

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Advanced Data Mining

This book consists of advanced information regarding data mining and their applications. It offers to aid data miners, researchers;

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Java Data Analysis

Get the most out of the popular Java libraries and tools to perform efficient data analysis About This Book * Get your basics right;

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Data Analysis and Data Mining Using Microsoft Business Intelligence Tools

Data Analysis and Data Mining using Microsoft Business Intelligence Tools enables analysts, power users, and business decision makers to;

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Java Transaction Design Strategies

Understanding how transaction management works in Java and developing an effective transaction design strategy can help to avoid data;

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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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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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Java

power of Java * Explore, analyse, and visualize your data effectively using easy-to-follow examples * A highly practical course covering a broad;

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Data Structures in Java

Simon Gray's consistent and coherent approach to data structures teaches students to focus on software design and testing as they learn to;

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Mastering Concurrency Programming with Java 9 -

the Java 9 Concurrency API and its new components * Improve the performance of your applications and process more data at the same time;

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Data Mining and Predictive Analysis

anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive;

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Developing Econometrics

that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It;

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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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