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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 901–925 of 2050 papers

TitleStatusHype
Causal Falling Rule Lists—0
Federated Model Search via Reinforcement Learning—0
A Review of Cross-Sectional Matrix Exponential Spatial Models—0
How to select predictive models for causal inference?—0
Aggregation of Affine Estimators—0
A coupled-mechanisms modelling framework for neurodegeneration—0
Federated Learning with Correlated Data: Taming the Tail for Age-Optimal Industrial IoT—0
hv-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)—0
Hybrid methodology based on Bayesian optimization and GA-PARSIMONY to search for parsimony models by combining hyperparameter optimization and feature selection—0
Improving classification performance by feature space transformations and model selection—0
Causal Discovery in Hawkes Processes by Minimum Description Length—0
Feature Selection Methods for Cost-Constrained Classification in Random Forests—0
Feature-based model selection for object detection from point cloud data—0
Causal Covariate Shift Correction using Fisher information penalty—0
A Review of Change of Variable Formulas for Generative Modeling—0
Fast sampling and model selection for Bayesian mixture models—0
Cats & Co: Categorical Time Series Coclustering—0
Fast rates with high probability in exp-concave statistical learning—0
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods—0
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory—0
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets—0
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow—0
Fast model selection by limiting SVM training times—0
Learning stable and predictive structures in kinetic systems: Benefits of a causal approach—0
Fast Linear Model Trees by PILOT—0
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