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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/western-oc2-lab/autonomouscyber-automl-based-autonomous-intrusion-detection-system

공식 코드

Towards Autonomous Cybersecurity: An Intelligent AutoML Framework for Autonomous Intrusion Detection

https://github.com/whatashot/excelformer

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ExcelFormer: A neural network surpassing GBDTs on tabular data

https://github.com/xanderjc/synthetic-model-combination

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Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning

https://github.com/xuzhao0/model-selection-reasoning

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Automatic Model Selection with Large Language Models for Reasoning

https://github.com/xxgege/nico-plus

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NICO++: Towards Better Benchmarking for Domain Generalization

https://github.com/xyvivian/hyper

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Fast Unsupervised Deep Outlier Model Selection with Hypernetworks

https://github.com/xyvivian/robod

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Hyperparameter Sensitivity in Deep Outlier Detection: Analysis and a Scalable Hyper-Ensemble Solution

https://github.com/yandex-research/tabred

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TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

https://github.com/yarotsky/gtapprox_benchmark

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GTApprox: surrogate modeling for industrial design

https://github.com/ydecastro/lar_testing

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Multiple Testing and Variable Selection along the path of the Least Angle Regression

https://github.com/yhzhu99/ehr-llm-benchmark

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ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks

https://github.com/yingcong-li/transformers-as-algorithms

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Transformers as Algorithms: Generalization and Stability in In-context Learning

https://github.com/yinlou/mltk

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Sparse Partially Linear Additive Models

https://github.com/yisuanwang/idea23d

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Idea23D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs

https://github.com/yiyhuang3/cate_estimator_selection

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Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators

https://github.com/ylincen/palm

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Unsupervised Discretization by Two-dimensional MDL-based Histogram

https://github.com/ymlasu/PeSBL_PDE_Learning

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Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential Equations

https://github.com/yng314/xai_for_wildfire

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Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data

https://github.com/ynlin11/filter

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Modeling High-Dimensional Data with Unknown Cut Points: A Fusion Penalized Logistic Threshold Regression

https://github.com/youngser/dhatkhat

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Simultaneous Dimensionality and Complexity Model Selection for Spectral Graph Clustering

https://github.com/ys-zong/medfair

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MEDFAIR: Benchmarking Fairness for Medical Imaging

https://github.com/yushu-li/hiltta

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Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection

https://github.com/yusonghust/HierarchicyBandit

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Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations

https://github.com/yuxinc17/set_valued_mtpp

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Probabilistic Modeling for Sequences of Sets in Continuous-Time

https://github.com/yxjdarren/mvdscn

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Multi-view Deep Subspace Clustering Networks

https://github.com/yyzharry/subpopbench

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Change is Hard: A Closer Look at Subpopulation Shift

https://github.com/yzhao062/elect

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Toward Unsupervised Outlier Model Selection

https://github.com/yzhao062/metaod

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Automating Outlier Detection via Meta-Learning

https://github.com/yzhao062/pyod

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PyOD 2: A Python Library for Outlier Detection with LLM-powered Model Selection

https://github.com/zamaex96/Spoof-Detect-Using-ViT

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Face Spoofing Detection using Deep Learning

https://github.com/zeyuzhangzyz/axiomvision

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AxiomVision: Accuracy-Guaranteed Adaptive Visual Model Selection for Perspective-Aware Video Analytics

https://github.com/zhangq327/arc

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Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap

https://github.com/zhaoxuli123/aetnet

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You Only Train Once: Learning a General Anomaly Enhancement Network with Random Masks for Hyperspectral Anomaly Detection

https://github.com/zhoukanglei/twinmultipath

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Solution Path Algorithm for Twin Multi-class Support Vector Machine

https://github.com/zhuxinqimac/PS-SC

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Where and What? Examining Interpretable Disentangled Representations

https://github.com/zju-daily/mmq

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Finding Materialized Models for Model Reuse

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