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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 976–1000 of 2050 papers

TitleStatusHype
Interpretable Machine Learning for Self-Service High-Risk Decision-Making—0
Fast and fully-automated histograms for large-scale data sets—0
Capturing and incorporating expert knowledge into machine learning models for quality prediction in manufacturing—0
Fair Community Detection and Structure Learning in Heterogeneous Graphical Models—0
Capitalizing on a Crisis: A Computational Analysis of all Five Million British Firms During the Covid-19 Pandemic—0
MF-CLIP: Leveraging CLIP as Surrogate Models for No-box Adversarial Attacks—0
fairml: A Statistician's Take on Fair Machine Learning Modelling—0
Can We Use Gradient Norm as a Measure of Generalization Error for Model Selection in Practice?—0
Factors in Fashion: Factor Analysis towards the Mode—0
Model Selection for Inverse Reinforcement Learning via Structural Risk Minimization—0
Factorized Asymptotic Bayesian Inference for Latent Feature Models—0
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models—0
Can Pre-training Indicators Reliably Predict Fine-tuning Outcomes of LLMs?—0
Is F_1 Score Suboptimal for Cybersecurity Models? Introducing C_score, a Cost-Aware Alternative for Model Assessment—0
Ising Model Selection Using _1-Regularized Linear Regression: A Statistical Mechanics Analysis—0
Is it worth it? Budget-related evaluation metrics for model selection—0
Is K-fold cross validation the best model selection method for Machine Learning?—0
Factor-Augmented Regularized Model for Hazard Regression—0
Face Recognition using Optimal Representation Ensemble—0
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation—0
Joint Continuous and Discrete Model Selection via Submodularity—0
Face Recognition Using Deep Multi-Pose Representations—0
Can Large Language Models Capture Public Opinion about Global Warming? An Empirical Assessment of Algorithmic Fidelity and Bias—0
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews—0
FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering—0
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