Guide to evaluating performance of prediction models for recurrent clinical events by Laura J. Bonnett, Thomas Spain, Alexandra Hunt, Jane L. Hutton, Victoria Watson, Anthony G. Marson, John Blakey

“…Performance of models was evaluated via numerical (root mean square prediction error, mean absolute prediction error, and prediction bias) and graphical (calibration plots and Bland–Altman plots) approaches. …”
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Evaluation of risk factors and modern possibilities for prediction of preterm labour by A. O. Shevchenko, Yu. Ya. Krut

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Three-Dimensional Analysis of Seepage in Fractured Rock Masses and Evaluation of the Accuracy of Empirical Methods for Predicting Permeability in Cutoff Walls: A Case Study of Chamshir Dam by Alireza Baghbanan, Masoud Dararbi, Amirhosein Momeni, Ahmad Rahmani Shahraki, Amin Azhari

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Mitigating class imbalance in churn prediction with ensemble methods and SMOTE by R. Suguna, J. Suriya Prakash, H. Aditya Pai, T. R. Mahesh, Venkatesan Vinoth Kumar, Temesgen Engida Yimer

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Prediction of Concrete Compressive Strength and Slump by Machine Learning Methods by M. Timur Cihan

“…According to the evaluation metrics, such as the correlation coefficient, root mean squared error, and mean absolute error, the fuzzy logic method makes better predictions than any other regression method. …”
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Comparison of Machine Learning Methods for Menstrual Cycle Analysis and Prediction by Mutiara Khairunisa, Desak Made Sidantya Amanda Putri, I Gusti Ngurah Lanang Wijayakusuma

“…This study compares three machine learning methods—Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and Decision Tree—for analyzing and predicting menstrual cycles. …”
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A Survey of Machine Learning Methods for Time Series Prediction by Timothy Hall, Khaled Rasheed

“…This study provides a comprehensive survey of the top-performing research papers in the field of time series prediction, offering insights into the most effective machine learning techniques, including tree-based, deep learning, and hybrid methods. …”
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A comprehensive survey of imbalanced learning methods for bankruptcy prediction by Tuong Le

“…The results show that the ensemble‐based model outperforms other methods in terms of bankruptcy prediction on the KB dataset.…”
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Advances in Traffic Congestion Prediction: An Overview of Emerging Techniques and Methods by Aristeidis Mystakidis, Paraskevas Koukaras, Christos Tjortjis

“…We examine several forecasting methods and discuss relative and absolute evaluation metrics from regression and classification perspectives. …”
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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

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Assessment of Machine Learning Methods for Concrete Compressive Strength Prediction by Oluwafemi Omotayo, Chinwuba Arum, Catherine Ikumapayi

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Evaluation and Optimization of Prediction Models for Crop Yield in Plant Factory by Yaoqi Peng, Yudong Zheng, Zengwei Zheng, Yong He

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Construction and evaluation of yeast expression networks by database-guided predictions by Katharina Papsdorf, Siyuan Sima, Gerhard Richter, Klaus Richter

“…We then show the ability of our networks to accurately predict further differentially expressed genes. Including these predicted genes into the networks improves the network quality and allows quantifying the predictive strength of the networks based on a newly implemented scoring method. …”
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Research on the Simulation Prediction and Evaluation of the Cathodic Protection Effect of Condensers by ZHANG Yu, LIU Ya - peng, LI Xiang - bo, LI Kai - wei, ZHANG Fan, TONG Hong - tao

“…Aiming at evaluating the cathodic protection effect of the condenser system, a prototype of the condenser system was established, and the protection effect of the cathodic protection system was evaluated through experiments. …”
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Simulating Gravitational Microlensing Events by TESS: Predictions on Statistics and Properties by Sedighe Sajadian, Atousa Kalantari, Hossein Fatheddin, Somayeh Khakpash

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Evaluation of Eurasian Snow Cover Fraction Prediction Based on BCC-CSM1.1m by Cheng Fei, Li Qiaoping, Shen Xinyong, Liu Yanju, Wang Jing

“…The model ability to predict Eurasian snow cover fraction (SCF) is evaluated by using the hindcast data during 1984-2019 from the Beijing Climate Center (BCC) Climate Prediction System version 2 (CPSv2), developed based on Climate System Model BCC-CSM1.1m. …”
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Prediction of the Characteristics of Concrete Containing Crushed Brick Aggregate by Marijana Hadzima-Nyarko, Miljan Kovačević, Ivanka Netinger Grubeša, Silva Lozančić

“…By testing various minimum leaf sizes and ensemble methods such as Random Forest and TreeBagger, the study evaluates metrics including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). …”
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Predictive Technology Assessment by Means of a Structure-Based Method of Machine Learning by Manja Mai-Ly PFAFF, Uwe FRIEß, Andreas OTTO, Matthias PUTZ

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Deep learning-based ranking method for subgroup and predictive biomarker identification in patients by Zihuan Liu, Yihua Gu, Xin Huang

“…In addition, DeepRAB enables model interpretability by facilitating predictive biomarker identification. We evaluate its performance using simulated datasets that vary in complexity, treatment effect strength, and sample size. …”
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An Interpretable Method for Anomaly Detection in Multivariate Time Series Predictions by Shijie Tang, Yong Ding, Huiyong Wang

“…Anomaly detection methods for industrial control networks using multivariate time series usually adopt deep learning-based prediction models. …”
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