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Practical Approaches to Causal Relationship Exploration

E-BookPDF1 - PDF WatermarkE-Book
80 Seiten
Englisch
Springer International Publishingerschienen am02.03.20152015
This brief presents four practical methods to effectively explore causal relationships, which are often used for explanation, prediction and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional independence tests for causal discovery. The last two methods employ association rule mining for efficient causal hypothesis generation, and a partial association test and retrospective cohort study for validating the hypotheses. All four methods are innovative and effective in identifying potential causal relationships around a given target, and each has its own strength and weakness. For each method, a software tool is provided along with examples demonstrating its use. Practical Approaches to Causal Relationship Exploration is designed for researchers and practitioners working in the areas of artificial intelligence, machine learning, data mining, and biomedical research. The material also benefits advanced students interested in causal relationship discovery.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR53,49
E-BookPDF1 - PDF WatermarkE-Book
EUR53,49

Produkt

KlappentextThis brief presents four practical methods to effectively explore causal relationships, which are often used for explanation, prediction and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional independence tests for causal discovery. The last two methods employ association rule mining for efficient causal hypothesis generation, and a partial association test and retrospective cohort study for validating the hypotheses. All four methods are innovative and effective in identifying potential causal relationships around a given target, and each has its own strength and weakness. For each method, a software tool is provided along with examples demonstrating its use. Practical Approaches to Causal Relationship Exploration is designed for researchers and practitioners working in the areas of artificial intelligence, machine learning, data mining, and biomedical research. The material also benefits advanced students interested in causal relationship discovery.
Details
Weitere ISBN/GTIN9783319144337
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis1 - PDF Watermark
FormatE107
Erscheinungsjahr2015
Erscheinungsdatum02.03.2015
Auflage2015
ReiheSpringerBriefs in Electrical and Computer Engineering
Seiten80 Seiten
SpracheEnglisch
IllustrationenX, 80 p. 55 illus.
Artikel-Nr.1721832
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
Introduction.- Local causal discovery with a simple PC algorithm.- A local causal discovery algorithm for high dimensional data.- Causal rule discovery with partial association test.- Causal rule discovery with cohort studies.- Experimental comparison and discussions.mehr

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