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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

Showing 551575 of 2050 papers

TitleStatusHype
The Economic Implications of Large Language Model Selection on Earnings and Return on Investment: A Decision Theoretic Model0
Comparative Study of Machine Learning Algorithms in Detecting Cardiovascular Diseases0
IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmarkCode0
Cross-Validated Off-Policy EvaluationCode0
AnyLoss: Transforming Classification Metrics into Loss FunctionsCode0
Symmetric Linear Bandits with Hidden SymmetryCode0
Green AI in Action: Strategic Model Selection for Ensembles in Production0
Simultaneous Identification of Sparse Structures and Communities in Heterogeneous Graphical Models0
Comparative Analysis of Predicting Subsequent Steps in Hénon Map0
Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations0
Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking0
Don't Waste Your Time: Early Stopping Cross-ValidationCode0
On Quantum Ambiguity and Potential Exponential Computational Speed-Ups to Solving Dynamic Asset Pricing Models0
Misclassification bounds for PAC-Bayesian sparse deep learning0
KITE: A Kernel-based Improved Transferability Estimation Method0
MRScore: Evaluating Radiology Report Generation with LLM-based Reward System0
Automated Model Selection for Generalized Linear Models0
Estimating the Number of Components in Finite Mixture Models via Variational Approximation0
mlr3summary: Concise and interpretable summaries for machine learning modelsCode0
On uncertainty-penalized Bayesian information criterion0
Generalizing Machine Learning Evaluation through the Integration of Shannon Entropy and Rough Set Theory0
A Sentiment Analysis of Medical Text Based on Deep Learning0
A Realistic Protocol for Evaluation of Weakly Supervised Object LocalizationCode0
On the Necessity of Collaboration for Online Model Selection with Decentralized Data0
Measuring Domain Shifts using Deep Learning Remote Photoplethysmography Model Similarity0
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