Software Defect Prediction through Neural Network and Feature Selections by Mutasem Shabeb Alkhasawneh

“…Precision, recall, F-measure, and accuracy are four methods used to evaluate the performance of the proposed methods. …”
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RNA secondary structure prediction by conducting multi-class classifications by Jiyuan Yang, Kengo Sato, Martin Loza, Sung-Joon Park, Kenta Nakai

“…In summary, we could produce valid predictions and achieve better performance without complex post-processing steps, and we show our additional methods are beneficial to the performance in within-RNA-family and cross-RNA-family evaluations.…”
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Predicting Court Judgment in Criminal Cases by Text Mining Techniques by Mohammad Farhadishad, Mohammad Kazemifard, Zahra Rezaei

“…Also, evaluation criteria were analyzed in situations where sentiment scores, emotional scores, or both were used in the prediction process along with judicial texts. …”
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Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions by Serdar Erisen

“…SERNet-Former_v2 has also been evaluated on challenging datasets of ADE20K, BDD100K, CamVid, and Cityscapes, showing significant advancements through attention-based methods. …”
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Predicting Crime Time Intervals Using Machine Learning Models by Arief Deswandi, Widi Hastomo

“…The evaluation was carried out using MAPE to measure the level of accuracy of crime clock predictions. …”
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RISK FACTORS AND PREDICTION OF MIOCARDIAL INFARCTION IN MALES OF DIFFERENT AGE by I. N. Suspitsina, I. A. Sukmanova

“…To conduct complex evaluation of MI risk factors in men taking their agespecific qualities, and to invent prediction calculator of MI based upon the data obtained.Material and methods. …”
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Predicting and comparing transcription start sites in single cell populations. by Shiwei Fu, Wei Vivian Li

“…Despite the emergence of computational methods designed to analyze 5' RNA sequencing data, current methods often lack comparative evaluations in single-cell contexts and are predominantly tailored for paired-end data, neglecting the potential of single-end data. …”
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Current Trends in Class Imbalance Learning for Software Defect Prediction by Somya R. Goyal

“…Researchers deployed a diverse range of learning methods to tackle the class-imbalance issues resulting into the remarkable achievements improving the performance of defect prediction models. …”
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Optimizing Learning: Predicting Research Competency via Statistical Proficiency by Tarid Wongvorachan, Siwachoat Srisuttiyakorn, Kanit Sriklaub

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Explainable models for predicting crab weight based on genetic programming by Tao Shi, Lingcheng Meng, Limiao Deng, Juan Li

“…The GP-based method has been evaluated on a publicly available dataset of crabs. …”
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Feature fusion with attributed deepwalk for protein–protein interaction prediction by Mei-Yuan Cao, Suhaila Zainudin, Kauthar Mohd Daud

“…The fused representations are then used to train classifiers for PPI prediction. Evaluation across three datasets using multiple classifiers demonstrated that FFADW significantly improves sample clustering and performs better than existing approaches, with the XGBoost classifier showing the best results. …”
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Machine Learning Techniques for Uncertainty Estimation in Dynamic Aperture Prediction by Carlo Emilio Montanari, Robert B. Appleby, Davide Di Croce, Massimo Giovannozzi, Tatiana Pieloni, Stefano Redaelli, Frederik F. Van der Veken

“…We evaluated these approaches to determine the most effective method for reliable uncertainty estimation in dynamic aperture predictions using machine learning techniques.…”
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Impact of computing platforms on classifier performance in heart disease prediction by Beenish Ayesha Akram, Muhammad Irfan, Amna Zafar, Sidra Khan, Rubina Shaheen

“…Our evaluation revealed that SVM achieves 77% accuracy when implemented using Scikit-Learn, demonstrating superiority over other methods. …”
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A nomogram to predict cancer-specific survival of ocular melanoma by Ruisheng Huang, Jian Chen, Limin Lin, Jun Lyu, Qing Zhou

“…Subsequently, an independent variable-based nomogram was developed. Finally, multiple methods were used to verify and evaluate the performance of the nomogram. …”
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Core-Level Modeling and Frequency Prediction for DSP Applications on FPGAs by Gongyu Wang, Greg Stitt, Herman Lam, Alan George

“…We evaluate CMD’s prediction methods using several high-performance DSP applications on various families of FPGAs and show an average clock-frequency prediction error of 3.6%, with a worst-case error of 20.4%, compared to the best of existing high-level prediction methods, 13.9% average error with 48.2% worst-case error. …”
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An adaptive spatiotemporal dynamic graph convolutional network for traffic prediction by Zhiguo Xiao, Qi Shen, Changgen Li, Dongni Li, Qian Liu

“…Experimental results on four public traffic datasets demonstrate that the AST-DGCN model achieves significant performance advantages over baseline methods across three critical evaluation metrics: root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE), thereby fully validating its superior predictive capabilities and competitive advantages.…”
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Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning by Motahare Shabestari, Akram Mehrabbeik, Sebastiano Barbieri, Pedro Marques-Vidal, Poria Heshmati-nasab, Reyhaneh Azizi

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Numerical Modeling and Analysis of Shadow Flicker Using Solar Path Functions for Enhanced Predictive Accuracy by Nicolai Radke, Patrick E. M. De Smet, Erika Ábrahám

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A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

“…We compared the predictive performance of each model through evaluation measures: RMSE, MASE, MAD. …”
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Gas well productivity prediction based on fractional Fourier transform by Chenchang Zheng, Jun Tang, Mengfan Li, Gewei Qi

“…In summary, the study reduces the cost of reservoir evaluation and can meet the demand of gas well productivity prediction.…”
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