Results 91 to 100 of about 962,663 (328)
A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design
IEEE Access, 2019 Decision trees are an extremely popular machine learning technique. Unfortunately, overfitting in decision trees still remains an open issue that sometimes prevents achieving good performance.
Rafael Garcia Leiva +3 more
doaj +1 more source
Building decision trees based on production knowledge as support in decision-making process
Production Engineering Archives, 2020 The article presents sources of production knowledge and thoroughly describes its identification which on the construction of decision trees, and on the construction of knowledge bases for production processes.
Matuszny Marcin
doaj +1 more source
Decision making with decision event graphs [PDF]
, 2010 We introduce a new modelling representation, the Decision Event Graph (DEG), for asymmetric multistage decision problems. The DEG explicitly encodes conditional independences and has additional significant advantages over other representations of ...
Cowell, Robert G. +2 more
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Simulation of Inhomogeneous Refractive Index Fields Induced by Hot Tailored Forming Components
Advanced Engineering Materials, EarlyView.This article presents a simulation model for simulating inhomogeneous refractive index fields (IRIF) in hot‐forged components, accounting for thermal influences and complex geometries. Through this simulation, a priori knowledge about the propagation of the IRIF can be obtained, allowing for the positioning of the component or an optical measurement ...
Pascal Kern +3 more
wiley +1 more source
Decision trees, monotone functions, and semimatroids [PDF]
, 2013 We define decision trees for monotone functions on a simplicial complex. We define homology decidability of monotone functions, and show that various monotone functions related to semimatroids are homology decidable.
White, Jacob A.
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Studies of Boosted Decision Trees for MiniBooNE Particle Identification
, 2005 Boosted decision trees are applied to particle identification in the MiniBooNE experiment operated at Fermi National Accelerator Laboratory (Fermilab) for neutrino oscillations.
Aguilar +17 more
core +2 more sources
Advanced Engineering Materials, EarlyView.In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source
Structured Learning of Tree Potentials in CRF for Image Segmentation
, 2017 We propose a new approach to image segmentation, which exploits the advantages of both conditional random fields (CRFs) and decision trees. In the literature, the potential functions of CRFs are mostly defined as a linear combination of some pre-defined ...
Lin, Guosheng +3 more
core +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source
Decision trees and prescriber choices
, 1994 Prescriber decisions are increasingly being pressured by a supply of economic information in the form of cost-effectivenessstudies, or similar evaluations, of a range of pharmaceuticals.
Stewart, A.
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