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Model Selection

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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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/hannahrosafriesacher/CalibrationStudy

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Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models

https://github.com/hanxudong/fair_enough

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Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP

https://github.com/haydenmct/predictive-equivalence

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Leveraging Predictive Equivalence in Decision Trees

https://github.com/haziqj/iprior-interaction

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Additive interaction modelling using I-priors

https://github.com/heaventian93/ImageNet-Models-on-Domain-Adaptation

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Impact of ImageNet Model Selection on Domain Adaptation

https://github.com/heidmic/suprb

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Investigating the Impact of Independent Rule Fitnesses in a Learning Classifier System

https://github.com/henrymoss/COLING2018

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Using J-K fold Cross Validation to Reduce Variance When Tuning NLP Models

https://github.com/henryyu23/das

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Towards Unsupervised Model Selection for Domain Adaptive Object Detection

https://github.com/hestiri/mlho

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Individualized Prediction of COVID-19 Adverse outcomes with MLHO

https://github.com/himelmallick/BayesRecipe

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The Reciprocal Bayesian LASSO

https://github.com/hiroki11x/timm_ood_calibration

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An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration

https://github.com/hlasse/data-centric-synthetic-data

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Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark

https://github.com/hmckay/botl

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Conceptually Diverse Base Model Selection for Meta-Learners in Concept Drifting Data Streams

https://github.com/huawei-noah/vega

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An Asymptotically Optimal Multi-Armed Bandit Algorithm and Hyperparameter Optimization

https://github.com/hugomalard/big-model-only-for-hard-audios

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Big model only for hard audios: Sample dependent Whisper model selection for efficient inferences

https://github.com/ianarawjo/ChainForge

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ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

https://github.com/idrl-lab/supervised_layout_benchmark

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A Deep Neural Network Surrogate Modeling Benchmark for Temperature Field Prediction of Heat Source Layout

https://github.com/imics-lab/time-series-embedding

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Time Series Embedding Methods for Classification Tasks: A Review

https://github.com/impresso/paraphrasus

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PARAPHRASUS : A Comprehensive Benchmark for Evaluating Paraphrase Detection Models

https://github.com/inria-thoth/edaa

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Entropic Descent Archetypal Analysis for Blind Hyperspectral Unmixing

https://github.com/irenetubikanec/mmlh

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Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length

https://github.com/j-adamczyk/ltp

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Strengthening structural baselines for graph classification using Local Topological Profile

https://github.com/ja-thomas/autoxgboost

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Automatic Gradient Boosting

https://github.com/jaeminyoo/dsv

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DSV: An Alignment Validation Loss for Self-supervised Outlier Model Selection

https://github.com/jeromerony/survey_wsl_histology

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Deep Weakly-Supervised Learning Methods for Classification and Localization in Histology Images: A Survey

https://github.com/jimgammell/gan_side_channel_leakage_detector

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Power side-channel leakage localization through adversarial training of deep neural networks

https://github.com/jo-wang/cal-sfda

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Cal-SFDA: Source-Free Domain-adaptive Semantic Segmentation with Differentiable Expected Calibration Error

https://github.com/jojacola/fuel

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Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit View

https://github.com/jr2021/ManyFairHPO-AIES

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A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes

https://github.com/juliabringewald/Solar-Flare-Forecast

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Solar Flare Forecast: A Comparative Analysis of Machine Learning Algorithms for Solar Flare Class Prediction

https://github.com/julienmartinelli/SADCBO

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Learning Relevant Contextual Variables Within Bayesian Optimization

https://github.com/jun-jie-huang/exeds

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Execution-based Evaluation for Data Science Code Generation Models

https://github.com/jungtaekkim/practical-bo-with-threshold-guided-mlm

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Practical Bayesian Optimization with Threshold-Guided Marginal Likelihood Maximization

https://github.com/junhongmit/H2GB

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When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark

https://github.com/jyansir/tmlp

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Team up GBDTs and DNNs: Advancing Efficient and Effective Tabular Prediction with Tree-hybrid MLPs

https://github.com/jzitovsky/sbv

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Revisiting Bellman Errors for Offline Model Selection

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