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Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

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Showing 1476–1500 of 2050 papers

TitleStatusHype
A Large Scale Evaluation of Distributional Semantic Models: Parameters, Interactions and Model Selection—0
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?—0
A Latent Gaussian Mixture Model for Clustering Longitudinal Data—0
eGAD! double descent is explained by Generalized Aliasing Decomposition—0
A linearized framework and a new benchmark for model selection for fine-tuning—0
ALMERIA: Boosting pairwise molecular contrasts with scalable methods—0
A Local Information Criterion for Dynamical Systems—0
A Machine Learning Approach to DoA Estimation and Model Order Selection for Antenna Arrays with Subarray Sampling—0
A Meta-learning based Distribution System Load Forecasting Model Selection Framework—0
SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems—0
A ModelOps-based Framework for Intelligent Medical Knowledge Extraction—0
A model selection approach for clustering a multinomial sequence with non-negative factorization—0
A Model Selection Approach for Corruption Robust Reinforcement Learning—0
A Multi-objective Exploratory Procedure for Regression Model Selection—0
A multi-stage machine learning model on diagnosis of esophageal manometry—0
An Algorithmic Framework for Computing Validation Performance Bounds by Using Suboptimal Models—0
Analysis of the AutoML Challenge Series 2015–2018—0
Analyzing Framing through the Casts of Characters in the News—0
Analyzing order flows in limit order books with ratios of Cox-type intensities—0
An Approach to the CLPsych 2018 Shared Task Using Top-Down Text Representation and Simple Bottom-Up Model Selection—0
An Asymptotic Equation Linking WAIC and WBIC in Singular Models—0
An AutoML-based approach for Network Intrusion Detection—0
An Axiomatic Approach to Model-Agnostic Concept Explanations—0
An Efficient Model Selection for Gaussian Mixture Model in a Bayesian Framework—0
An Empirical Investigation into Benchmarking Model Multiplicity for Trustworthy Machine Learning: A Case Study on Image Classification—0
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