In the study of decision-making, a fast-and-frugal tree is a simple graphical structure that categorizes objects by asking one question at a time. These decision trees are used in a range of fields: psychology, artificial intelligence, and management science. Unlike other decision or classification trees, such as Leo Breiman's CART, fast-and-frugal trees are intentionally simple, both in their construction as well as their execution, and operate speedily with little information. For this reason, fast-and-frugal-trees are potentially attractive when designing resource-constrained tasks
Attributes | Values |
---|
rdfs:label
| - Fast-and-frugal trees (en)
- Albero veloce e frugale (it)
|
rdfs:comment
| - In the study of decision-making, a fast-and-frugal tree is a simple graphical structure that categorizes objects by asking one question at a time. These decision trees are used in a range of fields: psychology, artificial intelligence, and management science. Unlike other decision or classification trees, such as Leo Breiman's CART, fast-and-frugal trees are intentionally simple, both in their construction as well as their execution, and operate speedily with little information. For this reason, fast-and-frugal-trees are potentially attractive when designing resource-constrained tasks (en)
- Un albero veloce e frugale è un tipo di albero di classificazione caratterizzato dalla presenza di almeno un nodo foglia per ogni livello. Gli alberi veloci e frugali vennero introdotti nel 2003 da Laura Martignon. Hanno come caratteristica peculiare la semplicità sia nell'esecuzione che nella costruzione, e costituiscono una sorta di euristica semplice nella classe degli strumenti adattativi postulati da e dal Centro per il Comportamento e la Cognizione Adattiva. Modelli simili erano stati precedentemente utilizzati da Martignon & Hoffrage, 1999; Green e Mehr, 1997; Dhami e Ayton, 2001; Dhami e Harries, 2001 e Fischer, Steiner, Zucol, Berger, Martignon, et al. 2002. (it)
|
foaf:depiction
| |
dcterms:subject
| |
Wikipage page ID
| |
Wikipage revision ID
| |
Link from a Wikipage to another Wikipage
| |
Link from a Wikipage to an external page
| |
sameAs
| |
dbp:wikiPageUsesTemplate
| |
thumbnail
| |
has abstract
| - In the study of decision-making, a fast-and-frugal tree is a simple graphical structure that categorizes objects by asking one question at a time. These decision trees are used in a range of fields: psychology, artificial intelligence, and management science. Unlike other decision or classification trees, such as Leo Breiman's CART, fast-and-frugal trees are intentionally simple, both in their construction as well as their execution, and operate speedily with little information. For this reason, fast-and-frugal-trees are potentially attractive when designing resource-constrained tasks Laura Martignon, Vitouch, Takezawa and Forster first introduced both the concept and the term in 2003; similar heuristics for other tasks had been used before, building on the formal models created by Gerd Gigerenzer and Herbert A. Simon. In categorization tasks with two options and m cues—also known as features or attributes—available for making such a decision, an FFT is defined as follows: A fast-and-frugal tree is a classification or a decision tree that has m+1 exits, with one exit for each of the first m -1 cues and two exits for the last cue. Mathematically, fast-and-frugal trees can be viewed as lexicographic heuristics or as linear classification models with non-compensatory weights and a threshold . Their formal properties and construction have also been analyzed using signal detection theory by Luan, Schooler and Gigerenzer in 2011 . (en)
- Un albero veloce e frugale è un tipo di albero di classificazione caratterizzato dalla presenza di almeno un nodo foglia per ogni livello. Gli alberi veloci e frugali vennero introdotti nel 2003 da Laura Martignon. Hanno come caratteristica peculiare la semplicità sia nell'esecuzione che nella costruzione, e costituiscono una sorta di euristica semplice nella classe degli strumenti adattativi postulati da e dal Centro per il Comportamento e la Cognizione Adattiva. Modelli simili erano stati precedentemente utilizzati da Martignon & Hoffrage, 1999; Green e Mehr, 1997; Dhami e Ayton, 2001; Dhami e Harries, 2001 e Fischer, Steiner, Zucol, Berger, Martignon, et al. 2002. Tuttavia, gli sviluppi recenti in diversi campi di applicazione hanno mantenuto la semplicità dell'esecuzione, introducendo procedure sofisticate e pertinenti per la costruzione che si sono dimostrati di estrema utilità nelle applicazioni. (it)
|
prov:wasDerivedFrom
| |
page length (characters) of wiki page
| |
foaf:isPrimaryTopicOf
| |
is Link from a Wikipage to another Wikipage
of | |
is Wikipage redirect
of | |
is foaf:primaryTopic
of | |