Prediction Accuracy

Prediction accuracy, the degree to which a model correctly anticipates outcomes, is a central concern across diverse scientific fields. Current research emphasizes improving accuracy by addressing challenges like data distribution shifts (e.g., using ensemble methods and uncertainty quantification with neural networks), mitigating randomness in data splitting (e.g., through interval estimation), and optimizing model efficiency (e.g., via adaptive basis function selection or hardware-aware ensemble selection). These advancements are crucial for enhancing the reliability and applicability of predictive models in various domains, from healthcare diagnostics to financial forecasting and autonomous systems.

Papers

December 13, 2023

Linear Combination of Exponential Moving Averages for Wireless Channel Prediction
Gabriele Formis, Stefano Scanzio, Gianluca Cena, Adriano Valenzano
Wireless Network Prediction Accuracy Prediction Model Channel Quality Linear Combination Wireless Channel Exponential Moving Average

December 2, 2023

When accurate prediction models yield harmful self-fulfilling prophecies
Wouter A.C. van Amsterdam, Nan van Geloven, Jesse H. Krijthe, Rajesh Ranganath, Giovanni Ciná
Data Driven Prediction Accuracy Harmful Content Prediction Model Model Development Predictive Power Accurate Predictive Model

November 22, 2023

Comparative Analysis of Linear Regression, Gaussian Elimination, and LU Decomposition for CT Real Estate Purchase Decisions
Xilin Cheng
Comparative Study Predictive Model Linear Regression Prediction Accuracy Investment Strategy Elimination Based Algorithm

October 25, 2023

Towards Continually Learning Application Performance Models
Ray A. O. Sinurat, Anurag Daram, Haryadi S. Gunawi, Robert B. Ross, Sandeep Madireddy
Prediction Accuracy High Performance Computing System Performance Model Distribution Drift

September 18, 2023

A performance characteristic curve for model evaluation: the application in information diffusion prediction
Wenjin Xie, Xiaomeng Wang, Radosław Michalski, Tao Jia
Application Proficiency System Performance Model Evaluation Prediction Accuracy Shannon Entropy Information Diffusion Random Data Principal Curve

August 27, 2023

Leveraging Linear Independence of Component Classifiers: Optimizing Size and Prediction Accuracy for Online Ensembles
Enes Bektas, Fazli Can
Prediction Accuracy Size Matter Linear Dependence Sub Component Level Segmentation Effective Ensemble Ensemble LLM Approach

August 21, 2023

DynED: Dynamic Ensemble Diversification in Data Stream Classification
Soheil Abadifard, Sepehr Bakhshi, Sanaz Gheibuni, Fazli Can
Concept Drift Ensemble Method Prediction Accuracy Ensemble Diversity Data Stream Classification Novel Ensemble LLM Ensemble

August 3, 2023

Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare
Eran Tal
Machine Learning Absolute Stance Bias Healthcare System Algorithmic Fairness Prediction Accuracy Counterfactual Prediction Systematic Bias

July 12, 2023

Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoring
Andreas Metzger, Tristan Kley, Aristide Rothweiler, Klaus Pohl
Adaptation Concern Prediction Accuracy accuratE Prediction Prescriptive Process Monitoring Efficient Prediction

June 30, 2023

Inter-case Predictive Process Monitoring: A candidate for Quantum Machine Learning?
Stefan Hill, David Fitzek, Patrick Delfmann, Carl Corea
Quantum Machine Learning Quantum Computer Predictive Performance Prediction Accuracy Quantum Machine Learning Model Multiple Candidate Predictive Process Monitoring

June 29, 2023

On the Predictive Accuracy of Neural Temporal Point Process Models for Continuous-time Event Data
Tanguy Bosser, Souhaib Ben Taieb
Real World Temporal Point Process Prediction Accuracy

June 26, 2023

Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition
Meena Jagadeesan, Michael I. Jordan, Jacob Steinhardt, Nika Haghtalab
Machine Learning Model Competition Platform Prediction Accuracy Data Representation Social Welfare Bayes Risk Positive Scaling

May 19, 2023

Distribution-Free Matrix Prediction Under Arbitrary Missing Pattern
Meijia Shao, Yuan Zhang
Conformal Prediction Prediction Accuracy Distribution Free Missingness Pattern Algorithmic Stability

May 14, 2023

Unraveling Cold Start Enigmas in Predictive Analytics for OTT Media: Synergistic Meta-Insights and Multimodal Ensemble Mastery
K. Ganguly, A. Patra
Predictive Model Model Selection Prediction Accuracy Ensemble Approach Synergistic Information Cold Start Novel Over the Air Second Multi Model Ensemble

May 13, 2023

Bridging History with AI A Comparative Evaluation of GPT 3.5, GPT4, and GoogleBARD in Predictive Accuracy and Fact Checking
Davut Emre Tasar, Ceren Ocal Tasar
Large Language Model Artificial Intelligence GPT 4 Fact Checking GPT Neo Prediction Accuracy Knowledge Gap History Representation

April 30, 2023

Time series clustering based on prediction accuracy of global forecasting models
Ángel López Oriona, Pablo Montero Manso, José Antonio Vilar Fernández
Prediction Accuracy Time Series Clustering Global Forecasting Clustering Performance Model Based Clustering Divisive Hierarchical Clustering Algorithm

April 24, 2023

Incorporating Experts' Judgment into Machine Learning Models
Hogun Park, Aly Megahed, Peifeng Yin, Yuya Ong, Pravar Mahajan, Pei Guo
Machine Learning Generative Adversarial Network Machine Learning Model Human Prediction Expert Knowledge Prediction Accuracy Human Intuition Legal Judgment

April 15, 2023

Learning in latent spaces improves the predictive accuracy of deep neural operators
Katiana Kontolati, Somdatta Goswami, George Em Karniadakis, Michael D. Shields
LeArning Abstract Deep Neural Network Latent Space Neural Operator Deep Operator Network Prediction Accuracy High Dimensional Partial Differential Equation Deep Neural Operator Operator Regression

January 27, 2023

Conformal inference is (almost) free for neural networks trained with early stopping
Ziyi Liang, Yanfei Zhou, Matteo Sesia
Neural Network Prediction Accuracy Early Stopping Conformal Inference Regularization Method Conformal Regression Holdout Set

January 17, 2023

Outlier-Based Domain of Applicability Identification for Materials Property Prediction Models
Gihan Panapitiya, Emily Saldanha
Machine Learning Model Feature Space Internet Service Domain Prediction Accuracy Model Prediction Material Property Prediction Applicability Study

Prediction Accuracy

Papers

Linear Combination of Exponential Moving Averages for Wireless Channel Prediction

When accurate prediction models yield harmful self-fulfilling prophecies

Comparative Analysis of Linear Regression, Gaussian Elimination, and LU Decomposition for CT Real Estate Purchase Decisions

Towards Continually Learning Application Performance Models

A performance characteristic curve for model evaluation: the application in information diffusion prediction

Leveraging Linear Independence of Component Classifiers: Optimizing Size and Prediction Accuracy for Online Ensembles

DynED: Dynamic Ensemble Diversification in Data Stream Classification

Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare

Automatically Reconciling the Trade-off between Prediction Accuracy and Earliness in Prescriptive Business Process Monitoring

Inter-case Predictive Process Monitoring: A candidate for Quantum Machine Learning?

On the Predictive Accuracy of Neural Temporal Point Process Models for Continuous-time Event Data

Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition

Distribution-Free Matrix Prediction Under Arbitrary Missing Pattern

Unraveling Cold Start Enigmas in Predictive Analytics for OTT Media: Synergistic Meta-Insights and Multimodal Ensemble Mastery

Bridging History with AI A Comparative Evaluation of GPT 3.5, GPT4, and GoogleBARD in Predictive Accuracy and Fact Checking

Time series clustering based on prediction accuracy of global forecasting models

Incorporating Experts' Judgment into Machine Learning Models

Learning in latent spaces improves the predictive accuracy of deep neural operators

Conformal inference is (almost) free for neural networks trained with early stopping

Outlier-Based Domain of Applicability Identification for Materials Property Prediction Models