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feature selection

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

https://github.com/shubhobm/e-values

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Feature Selection using e-values

https://github.com/shuzihuaiyu/tacfn

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TACFN: Transformer-based Adaptive Cross-modal Fusion Network for Multimodal Emotion Recognition

https://github.com/sigma10010/histo_img_seg

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Structure-aware scale-adaptive networks for cancer segmentation in whole-slide images

https://github.com/silversolver/robustatd

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Robust AI-Generated Text Detection by Restricted Embeddings

https://github.com/slds-lmu/paper_2023_eagga

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Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models

https://github.com/smashhadi/feature-selection-extraction

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Feature Selection and Feature Extraction in Pattern Analysis: A Literature Review

https://github.com/soerenab/AudioMNIST

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AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark

https://github.com/sramirez/spark-RELIEFFC-fselection

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BELIEF: A distance-based redundancy-proof feature selection method for Big Data

https://github.com/srigas/KAN_Fault_Diagnosis

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Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networks

https://github.com/srizon143005/pancreaticcancerbiomarkers

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Prognostic Biomarker Identification for Pancreatic Cancer by Analyzing Multiple mRNA Microarray and microRNA Expression Datasets

https://github.com/stan-dev/projpred

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Projective Inference in High-dimensional Problems: Prediction and Feature Selection

https://github.com/stanford-futuredata/wmsketch

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Sketching Linear Classifiers over Data Streams

https://github.com/starmpcc/remed

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General-Purpose Retrieval-Enhanced Medical Prediction Model Using Near-Infinite History

https://github.com/sthowling/alioth

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Alioth: A Machine Learning Based Interference-Aware Performance Monitor for Multi-Tenancy Applications in Public Cloud

https://github.com/suinleelab/dime

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Estimating Conditional Mutual Information for Dynamic Feature Selection

https://github.com/sunilkmaurya/FSGNN

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Improving Graph Neural Networks with Simple Architecture Design

https://github.com/svddchallenge/ctrsvdd2024_baseline

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CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake Detection

https://github.com/syitong/randfourier

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But How Does It Work in Theory? Linear SVM with Random Features

https://github.com/szmazurek/ds_assessment

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Assessing Dataset Quality Through Decision Tree Characteristics in Autoencoder-Processed Spaces

https://github.com/takumayagi/EK_Instance

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Object Instance Identification in Dynamic Environments

https://github.com/talcs/naap-440

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Accuracy Prediction for NAS Acceleration using Feature Selection and Extrapolation

https://github.com/tallamjr/astronet

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Paying Attention to Astronomical Transients: Introducing the Time-series Transformer for Photometric Classification

https://github.com/taohan10200/steerer

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STEERER: Resolving Scale Variations for Counting and Localization via Selective Inheritance Learning

https://github.com/tapilab/emnlp-2020-spurious

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Identifying Spurious Correlations for Robust Text Classification

https://github.com/terrenceckchan/carbon-trading-verfication

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Joint Study of Above Ground Biomass and Soil Organic Carbon for Total Carbon Estimation using Satellite Imagery in Scotland

https://github.com/tfjgeorge/ntk_alignment

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Implicit Regularization via Neural Feature Alignment

https://github.com/th-b/bla

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Bounded logit attention: Learning to explain image classifiers

https://github.com/the-garden-of-sinner/mdap

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MDAP: A Multi-view Disentangled and Adaptive Preference Learning Framework for Cross-Domain Recommendation

https://github.com/tianyic/obproxsg

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Orthant Based Proximal Stochastic Gradient Method for $\ell_1$-Regularized Optimization

https://github.com/tiiuae/gnn-jamming-source-localization

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Graph Neural Networks for Jamming Source Localization

https://github.com/tiwarylab/terp

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Thermodynamics-inspired Explanations of Artificial Intelligence

https://github.com/tobiaboschi/fasten

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FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions

https://github.com/tobiaboschi/ssnal_elastic

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An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net

https://github.com/transbiozi/mtlcomb

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MTLComb: multi-task learning combining regression and classification tasks for joint feature selection

https://github.com/transferwise/shap-select

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Shap-Select: Lightweight Feature Selection Using SHAP Values and Regression

https://github.com/tu184044109/VIDEVAL_release

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UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content

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