Results 291 to 300 of about 1,236,533 (310)
Using Evolutionary Algorithms to Induce Oblique Decision Trees
, 2000 Erick Cantú‐Paz, Chandrika Kamath
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Towards an automated classification phase in the software maintenance process using decision tree. [PDF]
PeerJ Comput SciAlturki S, Almoaiqel S.
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Correlation of visceral adiposity index and dietary profile with cardiovascular disease based on decision tree modeling: a cross-sectional study of NHANES. [PDF]
Eur J Med ResXu S, Cai Y, Hu H, Zhai C.
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Biomarker-derived fast-and-frugal decision tree for preemption of veno-occlusive disease/sinusoidal obstructive syndrome. [PDF]
Blood AdvPaczesny S, Hozo I, Djulbegovic B.
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Identifying intersectional groups at risk for missing breast cancer screening: Comparing regression- and decision tree-based approaches. [PDF]
SSM Popul HealthPedrós Barnils N, Schüz B.
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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
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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