Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications - Image 1

£27.99

Apress Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications

Name: Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications
Brand: Apress
Price: 27.99 GBP
Availability: InStock

Data Mining

Price History & Forecast

Last 1 days • 1 data points (No recent data available)

Historical

Generating forecast...

Not enough data points to display chart (need at least 2 points)

Price Distribution

Price distribution over 1 days • 1 price levels

Days at Price

Price Analysis

Most common price: £28 (1 days, 100.0%)

Price range: £28 - £28

Price levels: 1 different prices over 1 days

Description

Discover hidden relationships among the variables in your data, and learn how to exploit these relationships. This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications. All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code. Many of these techniques are recent developments, still not in widespread use. Others are standard algorithms given a fresh look. In every case, the focus is on practical applicability, with all code written in such a way that it can easily be included into any program. The Windows-based DATAMINE program lets you experiment with the techniques before incorporating them into your own work. What You'll Learn Use Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your data Discover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the data Work with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methods See how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the data Plot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is high Who This Book Is For Anyone interested in discovering and exploiting relationships among variables. Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.

Product Specifications

Brand: Apress
Format: paperback
ASIN: 148423314X
Category: Books > Subjects > Computing & Internet > Databases > Data Storage & Management > Data Mining
Domain: Amazon UK
Release Date: 19 December 2017
Listed Since: 05 October 2017

Barcode

No barcode data available

Apress Data Mining Algorithms in C++: Data Patterns and Algorithms for Modern Applications

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Modern Data Mining Algorithms in C++ and CUDA C: Recent Developments in Feature Extraction and Selection Algorithms for Data Science

Assessing and Improving Prediction and Classification: Theory and Algorithms in C++

Implementing Useful Algorithms in C++

Data Clustering in C++: An Object-Oriented Approach: 20 (Chapman & Hall/CRC Data Mining and Knowledge Discovery)

Data Mining: The Textbook

Data Mining: The Textbook

John Wiley & Sons Data Mining and Machine Learning Applications

Data Mining: Theories, Algorithms, and Examples (Human Factors and Ergonomics)

Data Classification: Algorithms and Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Practical Graph Mining with R (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Principles and Theories of Data Mining With RapidMiner

Design and Implementation of Data Mining Tools

Predictive Analytics and Data Mining: Concepts and Practice with RapidMiner

Data Mining in Crystallography: 134 (Structure and Bonding, 134)

Data Mining in Crystallography: 134 (Structure and Bonding, 134)

Algorithms for Data Science

Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines

CRC Press Data Clustering: Algorithms and Applications Book

Learn Data Mining Through Excel: A Step-by-Step Approach for Understanding Machine Learning Methods

Data Mining with Python: Theory, Application, and Case Studies (Chapman & Hall/CRC The Python Series)

Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)

Practical Data Mining

Data Mining Methods and Applications (Discrete Mathematics and Its Applications)

Advanced Data Mining Techniques