ISBN: 9783319144320 - practical approaches to causal relationship exploration (springerbriefs in electrical and computer engineering) (14 resultados)

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Taschenbuch. Condición: Neu. Practical Approaches to Causal Relationship Exploration | Jiuyong Li (u. a.) | Taschenbuch | SpringerBriefs in Electrical and Computer Engineering | x | Englisch | 2015 | Springer | EAN 9783319144320 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 92 pp. Englisch. …

Condición: New. Print on Demand pp. 80.

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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 ap. …

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 92 pp. Englisch. …