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regression

Papers

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Showing 3851–3875 of 9424 papers

TitleStatusHype
HkAmsters at CMCL 2022 Shared Task: Predicting Eye-Tracking Data from a Gradient Boosting Framework with Linguistic Features—0
COMBATANT@TamilNLP-ACL2022: Fine-grained Categorization of Abusive Comments using Logistic Regression—0
CMCL 2022 Shared Task on Multilingual and Crosslingual Prediction of Human Reading Behavior—0
Empathy and Distress Prediction using Transformer Multi-output Regression and Emotion Analysis with an Ensemble of Supervised and Zero-Shot Learning Models—0
SOA_NLP@LT-EDI-ACL2022: An Ensemble Model for Hope Speech Detection from YouTube Comments—0
Ridgeless Regression with Random FeaturesCode0
Deep vs. Shallow Learning: A Benchmark Study in Low Magnitude Earthquake Detection—0
Learning Localization-aware Target Confidence for Siamese Visual Tracking—0
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models—0
A study of tree-based methods and their combination—0
Taylor Genetic Programming for Symbolic Regression—0
Neighbor-Based Optimized Logistic Regression Machine Learning Model For Electric Vehicle Occupancy Detection—0
Probabilistic Models for Manufacturing Lead Times—0
An Explainable Regression Framework for Predicting Remaining Useful Life of Machines—0
Impulse response estimation via flexible local projections—0
Asymptotic Inference for Infinitely Imbalanced Logistic Regression—0
ISTRBoost: Importance Sampling Transfer Regression using Boosting—0
Forecasting foreign exchange rates with regression networks tuned by Bayesian optimization—0
Coefficient Mutation in the Gene-pool Optimal Mixing Evolutionary Algorithm for Symbolic Regression—0
A PAC-Bayes oracle inequality for sparse neural networks—0
The Galactic 3D large-scale dust distribution via Gaussian process regression on spherical coordinates—0
Transformation-Interaction-Rational Representation for Symbolic RegressionCode0
Predicting Sleeping Quality using Convolutional Neural Networks—0
Double Machine Learning Methods for Estimating Average Treatment Effects: A Comparative StudyCode0
Local Gaussian process extrapolation for BART models with applications to causal inference—0
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All datasetsCalifornia Housing PricesConcrete Compressive StrengthMedical Cost Personal DatasetSynthetic: y = x * sin xADORECar_Price_Prediction

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.79—Unverified
2Baseline RegressionR2 Score0.58—Unverified
3Mimic / SurrogateR2 Score0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.86—Unverified
2Baseline RegressionR2 Score0.59—Unverified
3Mimic / SurrogateR2 Score0.58—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.87—Unverified
2Baseline RegressionR2 Score0.78—Unverified
3Mimic / SurrogateR2 Score0.78—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.98—Unverified
2Baseline RegressionR2 Score-0.01—Unverified
3Mimic / SurrogateR2 Score-0.01—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoost-MACCSmicro-averaged RMSE0.93—Unverified
2RF-ToxPrintchemical macro-average RMSE0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1Linear and Decision Tree RegressionR Squared86.84—Unverified