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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 1951–1975 of 2050 papers

TitleStatusHype
FIB: A Method for Evaluation of Feature Impact Balance in Multi-Dimensional Data—0
Find the dimension that counts: Fast dimension estimation and Krylov PCA—0
Fine-Tuning Video Transformers for Word-Level Bangla Sign Language: A Comparative Analysis for Classification Tasks—0
Fitting Multiple Heterogeneous Models by Multi-Class Cascaded T-Linkage—0
Fitting Sparse Markov Models to Categorical Time Series Using Regularization—0
Fitting very flexible models: Linear regression with large numbers of parameters—0
Fixed effects testing in high-dimensional linear mixed models—0
Forecasting large collections of time series: feature-based methods—0
Forecasting Whole-Brain Neuronal Activity from Volumetric Video—0
Forward and Backward Feature Selection for Query Performance Prediction—0
Forward utilities and Mean-field games under relative performance concerns—0
Foundation of Calculating Normalized Maximum Likelihood for Continuous Probability Models—0
Frame Fusion with Vehicle Motion Prediction for 3D Object Detection—0
From Human Annotation to LLMs: SILICON Annotation Workflow for Management Research—0
From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs—0
Functional additive models on manifolds of planar shapes and forms—0
Fundamental limits to learning closed-form mathematical models from data—0
Fusion Subspace Clustering for Incomplete Data—0
Fuzzy Fibers: Uncertainty in dMRI Tractography—0
Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles—0
Gaussian Mixture Clustering Using Relative Tests of Fit—0
Gaussian Process-based Spatial Reconstruction of Electromagnetic fields—0
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria—0
General Bayesian time-varying parameter VARs for predicting government bond yields—0
General Hannan and Quinn Criterion for Common Time Series—0
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