Results 271 to 280 of about 883,011 (303)
Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities. [PDF]
J Pathol InformGonzalez R +5 more
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Using Evolutionary Algorithms to Induce Oblique Decision Trees
, 2000 Erick Cantú‐Paz, Chandrika Kamath
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Immediate postnatal prediction of death or bronchopulmonary dysplasia among very preterm and very low birth weight infants based on gradient boosting decision trees algorithm: A nationwide database study in Japan. [PDF]
PLoS OneYoneda K +5 more
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Medical management or surgery for acute cholecystitis: Enhancing treatment selection with decision trees. [PDF]
Ulus Travma Acil Cerrahi DergSezikli İ +4 more
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Economic Theory, 2005 The traditional model of sequential decision making, for instance, in extensive form games, is a tree. Most texts define a tree as a connected directed graph without loops and a distinguished node, called the root. But an abstract graph is not a domain for decision theory.
Alós-Ferrer, C., Ritzberger, K.
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2009
Decision Tree Induction (DTI) is a tool to induce a classification or regression model from (usually large) datasets characterized by n objects (records), each one containing a set x of numerical or nominal attributes, and a special feature y designed as its outcome. Statisticians use the terms “predictors” to identify attributes and “response variable”
SICILIANO, ROBERTA, CONVERSANO, CLAUDIO
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Decision Tree Induction (DTI) is a tool to induce a classification or regression model from (usually large) datasets characterized by n objects (records), each one containing a set x of numerical or nominal attributes, and a special feature y designed as its outcome. Statisticians use the terms “predictors” to identify attributes and “response variable”
SICILIANO, ROBERTA, CONVERSANO, CLAUDIO
openaire +3 more sources
WIREs Computational Statistics, 2013
Decision trees trace their origins to the era of the early development of written records. This history illustrates a major strength of trees: exceptionally interpretable results which have an intuitive tree‐like display which, in turn, enhances understanding and the dissemination of results. The computational origins of decision trees—sometimes called
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Decision trees trace their origins to the era of the early development of written records. This history illustrates a major strength of trees: exceptionally interpretable results which have an intuitive tree‐like display which, in turn, enhances understanding and the dissemination of results. The computational origins of decision trees—sometimes called
openaire +2 more sources
Intelligent Data Analysis, 2000
Summary: The article presents the extension of a common decision tree concept to a multidimensional -- vector -- decision tree constructed with the help of evolutionary techniques. In contrary to the common decision tree the vector decision tree can make more than just one suggestion per input sample.
Šprogar, Matej +4 more
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Summary: The article presents the extension of a common decision tree concept to a multidimensional -- vector -- decision tree constructed with the help of evolutionary techniques. In contrary to the common decision tree the vector decision tree can make more than just one suggestion per input sample.
Šprogar, Matej +4 more
openaire +3 more sources