Results 61 to 70 of about 79,652 (190)
evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R [PDF]
Commonly used classification and regression tree methods like the CART algorithm are recursive partitioning methods that build the model in a forward stepwise search.
Karl-Peter Pfeiffer +2 more
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Patient Preference and Adherence, 2018 Pierre Michel,1,2 Karine Baumstarck,1 Anderson Loundou,1 Badih Ghattas,2 Pascal Auquier,1 Laurent Boyer1 1Aix-Marseille Univ, School of Medicine, CEReSS - Health Service Research and Quality of Life Center, Marseille, France; 2Mathematics Institute of ...
Michel P +5 more
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Classification and regression trees (CART) for predicting factors associated with RLS.
, 2020 Classification and regression trees (CART) for predicting factors associated with RLS.
Atsushi Kawakami (398370) +5 more
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Media Statistika, 2014 Credit is the greatest asset managed the bank and also the most dominant contributor to the bank’s revenue. Debtors to pay their credit to the bank may smoothly or jammed. This study aims to identify the variables that affect a debtor’s credit status and
Agung Waluyo +2 more
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Decision Trees and Their Application for Classification and Regression Problems [PDF]
, 2019 Tree methods are some of the best and most commonly used methods in the field of statistical learning. They are widely used in classification and regression modeling.
Njoku, Obinna Chilezie
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Splitting criteria for regression trees
, 1996 Breiman, Friedman, Olshen and Stone (1984) expounded a method called Classification and Regression Trees, or CART, which can be used for nonparametric discrimination and regression.
Taylor, Paul C., Jones, M. C.
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Folia Oeconomica Stetinensia, 2020 Research background: The efficiency of the functioning of District Employment Agencies is often assessed on the basis of the level of employment and cost-effectiveness indices. The values of these indices are influenced by various socio-economic factors,
Bąk Iwona +2 more
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A Comparison of Classification/Regression Trees and Logistic Regression in Failure Models
Procedia Economics and Finance, 2015 The use of non-parametric statistical methods, the development of models geared towards the homogeneous characteristics of corporate sub-populations, and the introduction of non-financial variables, are three main issues analysed in this paper. This study compares the predictive performance of a non-parametric methodology, namelyClassification ...
Irimia Diéguez, Ana Isabel +2 more
openaire +3 more sources
Applying CHAID for logistic regression diagnostics and classification accuracy improvement [PDF]
In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: 1. How to automatically detect segments in which the
Antipov, Evgeny, Pokryshevskaya, Elena
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, 2022 Materials to accompany chapter in Data and Methods in Corpus Linguistics (Cambridge University Press) - Comparing logistic regression, multinomial regression, classification trees and random forests applied to ternary variables: Three-way genitive ...
Benedikt Szmrecsanyi, Matthew Fahy
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