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regression

Papers

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Showing 7676–7700 of 9424 papers

TitleStatusHype
Application of Common Spatial Patterns in Gravitational Waves Detection—0
Application of computer simulation results and machine learning in analysis of microwave radiothermometry data—0
Application of Deep Learning for Factor Timing in Asset Management—0
Application of Gaussian Process Regression to Koopman Mode Decomposition for Noisy Dynamic Data—0
Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock—0
Application of Random Forest and Support Vector Machine for Investigation of Pressure Filtration Performance, a Zinc Plant Filter Cake Modeling—0
Application of Support Vector Machine Modeling and Graph Theory Metrics for Disease Classification—0
Applications of Machine Learning in Fintech Credit Card Fraud Detection—0
Applying Bayesian Ridge Regression AI Modeling in Virus Severity Prediction—0
Applying Regression Conformal Prediction with Nearest Neighbors to time series data—0
Applying SVGD to Bayesian Neural Networks for Cyclical Time-Series Prediction and Inference—0
Approximate Bayes learning of stochastic differential equations—0
Approximate cross-validation formula for Bayesian linear regression—0
Approximated Orthogonal Projection Unit: Stabilizing Regression Network Training Using Natural Gradient—0
Approximate Gaussian process inference for the drift function in stochastic differential equations—0
Approximate Inference for Nonstationary Heteroscedastic Gaussian process Regression—0
Approximate Leave-one-out Cross Validation for Regression with _1 Regularizers (extended version)—0
Approximate Steepest Coordinate Descent—0
Approximating Optimal Estimation of Time Offset Synchronization with Temperature Variations—0
Approximating Score-based Explanation Techniques Using Conformal Regression—0
Approximation bounds for norm constrained neural networks with applications to regression and GANs—0
Approximation Bounds for Recurrent Neural Networks with Application to Regression—0
Approximation Bounds for Transformer Networks with Application to Regression—0
Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions—0
Approximation of RKHS Functionals by Neural Networks—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