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Computational Methods of Feature Selection

ISBN/GTIN

Computational Methods of Feature Selection

von

Liu, HuanHrsg.Motoda, HiroshiHrsg.

BuchGebunden

Verkaufsrang8449in

CHF160.00

In den Warenkorb

Beschreibung

Feature selection is an essential step for successful data mining applications and has practical significance in many areas, such as statistics, pattern recognition, machine learning, and knowledge discovery. This book covers the key concepts, representative approaches, and inventive applications of various aspects of feature selection.

Weitere Beschreibungen

Details

ISBN/GTIN978-1-58488-878-9

ProduktartBuch

EinbandGebunden

VerlagTaylor and FrancisChapman and Hall/CRC

Erscheinungsdatum29.10.2007

Auflage1. A.

ReiheChapman & Hall/CRC Data Mining and Knowledge Discovery Series

SpracheEnglisch

MasseBreite 156 mm, Höhe 234 mm

Gewicht771 g

IllustrationenFarb., s/w. Abb.

Artikel-Nr.5006596

KatalogBuchzentrum

Datenquelle-Nr.23093242

Weitere Details

Reihe

Computational Methods of Feature Selection

Understanding Complex Datasets

Knowledge Discovery for Counterterrorism and Law Enforcement

Multimedia Data Mining

Constrained Clustering

Information Discovery on Electronic Health Records

Data Mining for Design and Marketing

Geographic Data Mining and Knowledge Discovery

The Top Ten Algorithms in Data Mining

Text Mining

Biological Data Mining

Statistical Data Mining Using SAS Applications

Knowledge Discovery from Data Streams

Handbook of Educational Data Mining

Mining Software Specifications

Spectral Feature Selection for Data Mining

Music Data Mining

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Advances in Machine Learning and Data Mining for Astronomy

Support Vector Machines

Contrast Data Mining

Data Clustering

RapidMiner

Computational Business Analytics

Computational Intelligent Data Analysis for Sustainable Development

Data Classification

Graph-Based Social Media Analysis

Event Mining

Accelerating Discovery

Healthcare Data Analytics

Text Mining and Visualization

Advances in Machine Learning and Data Mining for Astronomy

Data Mining with R

Data Science and Analytics with Python

Large-Scale Machine Learning in the Earth Sciences

Data Science and Analytics with Python

Social Networks with Rich Edge Semantics

Data Mining for Design and Marketing

Mining Software Specifications

Biological Data Mining

Autor

Liu, HuanHrsg.Motoda, HiroshiHrsg.

Arizona State University, Tempe, AZ AFOSR/AOARD, Tokyo, Japan

Weitere Produkte von Liu, Huan

Hrsg.

Social Computing, Behavioral Modeling, and Prediction

Social Computing and Behavioral Modeling

Spectral Feature Selection for Data Mining

Feature Engineering for Machine Learning and Data Analytics

Spectral Feature Selection for Data Mining

Multichannel Retailing

Social Media Mining

Social Computing and Behavioral Modeling

Social Computing, Behavioral Modeling, and Prediction

Twitter Data Analytics

Feature Engineering for Machine Learning and Data Analytics

Disinformation, Misinformation, and Fake News in Social Media

Combating Online Hostile Posts in Regional Languages during Emergency Situation

Disinformation, Misinformation, and Fake News in Social Media

Phänomenologie des Unsichtbaren

Modeling and Data Mining in Blogosphere

Community detection and mining in social media

Provenance Data in Social Media

Mining Human Mobility in Location-Based Social Networks

Detecting Fake News on Social Media

Trust in Social Media

Trust in Social Media

Detecting Fake News on Social Media

Modeling and Data Mining in Blogosphere

Mining Human Mobility in Location-Based Social Networks

Community detection and mining in social media

Provenance Data in Social Media

Combating Online Hostile Posts in Regional Languages during Emergency Situation

Disinformation, Misinformation, and Fake News in Social Media

Feature Engineering for Machine Learning and Data Analytics

Weitere Produkte von Motoda, Hiroshi

Hrsg.

Discovery Science

Active Mining - New Directions of Data Mining

Instance Selection and Construction for Data Mining

Discovery Science

PRICAI'98: Topics in Artificial Intelligence

Feature Selection for Knowledge Discovery and Data Mining

Instance Selection and Construction for Data Mining

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Feature Extraction, Construction and Selection

Feature Selection for Knowledge Discovery and Data Mining

Behavior and Social Computing

Advanced Data Mining and Applications

Advanced Data Mining and Applications

Rough Sets and Intelligent Systems Paradigms

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Feature Extraction, Construction and Selection

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Rough Sets and Intelligent Systems Paradigms

Behavior and Social Computing

Advanced Data Mining and Applications

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Instance Selection and Construction for Data Mining

Advanced Data Mining and Applications

Feature Selection for Knowledge Discovery and Data Mining

Feature Extraction, Construction and Selection

Active Mining

Schlagworte

AudienceCode

Professional and scholarly: For an expert adult audience, including professional development and academic research. (06)

BIC

Dewey Decimal

LC Class

QA76.9.D3 C64 2008

THEMA Schlagwort

Datenbanken (UN)

THEMA Hauptschlagwort

Datenbanken (UN)

UKSLC