Achievements of Rseslib KNN reported in independent reviewed publications

Rank Out of Task Reference
2
10
 Gait analysis for rehabilitation planning Galasso, S., Baptista, R., Molinara, M., Pizzocaro, S., Calabro, R. S., & De Nunzio, A. M. (2023). Predicting physical activity levels from kinematic gait data using machine learning techniques. Engineering Applications of Artificial Intelligence (Vol. 123, 106487).
2
5
 Student performance prediction Niu, K., Jia, B. T., Zou, Y. H., & Lu, G. Q. (2022). A hybrid model for predicting academic performance of engineering undergraduates. International Journal of Modeling, Simulation, and Scientific Computing (Vol. 14, No. 02, 2350030).
2
13
 Phlebopathic patient screening D'Angelantonio, E., Lucangeli, L., Camomilla, V., & Pallotti, A. (2022). Smart sock-based machine learning models development for phlebopathic patient screening. IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) (pp. 137-142). IEEE.
2
47
 Metabolic pathway prediction of plant enzymes de Oliveira Almeida, R., & Valente, G. T. (2020). Predicting metabolic pathways of plant enzymes without using sequence similarity: Models from machine learning. In The Plant Genome (Vol. 13, Issue 3). Wiley.
5
47
 Student performance prediction Almasri, A., Celebi, E., & Alkhawaldeh, R. S. (2019). EMT: Ensemble meta-based tree model for predicting student performance. Scientific Programming, 2019.
2
8
 Context awareness of a service robot Grama, L., & Rusu, C. (2018). Adding audio capabilities to TIAGo service robot. In 2018 International Symposium on Electronics and Telecommunications (ISETC) (pp. 1-4). IEEE.
1
21
 Facebook content recognition Dey, N., Borah, S., Babo, R., & Ashour, A. (2018). Social network analytics: computational research methods and techniques. Academic Press.
2
8
 Acoustic-based environment monitoring Rusu, C., & Grama, L. (2017). Recent developments in acoustical signal classification for monitoring. In 2017 5th International Symposium on Electrical and Electronics Engineering (ISEEE) (pp. 1-10). IEEE.
1
9
 Environmental sound recognition Grama, L., & Rusu, C. (2017). Choosing an accurate number of mel frequency cepstral coefficients for audio classification purpose. In Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis (pp. 225-230). IEEE.

Achievements of Local KNN reported in independent reviewed publications

Rank Out of Task Reference
1
5
 Air compressor fault prediction Nambiar, A., Venkatesh, S. N., Aravinth, S., Sugumaran, V., Ramteke, S., M., & Marian, M. (2024). Prediction of air compressor faults with feature fusion and machine learning. Knowledge-Based Systems (Vol. 304, 112519).
1
5
 Clutch fault diagnosis Nair, S., Sridharan, N. V., Chakrapani, G., & Vaithiyanathan, S. (2024). Automotive clutch fault diagnosis through feature fusion and lazy family of classifiers. Journal of Vibration Engineering & Technologies, 2024 (pp. 1-14).
1
18
 Driver stress prediction Al-Nashashibi, M. Y., El-Khalili, N., Hadi, W., Al-Banna, A. K., & Issa, G. (2023). Identifying the most significant features for stress prediction of automobile drivers: a comprehensive study. Journal of Information & Knowledge Management (2350064).
3
11
 Obesity prediction Cheng, X., Lin, S., Liu, J., Liu, S., Zhang, J., Nie, P., Fuemmeler, B. F., Wang, Y., & Xue, H. (2021). Does physical activity predict obesity - a machine learning and statistical method-based analysis. International Journal of Environmental Research and Public Health (Vol. 18, Issue 8, 3966).
5
47
 Student performance prediction Almasri, A., Celebi, E., & Alkhawaldeh, R. S. (2019). EMT: Ensemble meta-based tree model for predicting student performance. Scientific Programming, 2019.

Achievements of Rough Set classifier reported in independent reviewed publications

Rank Out of Task Reference
1
5
 Hotel quality prediction Cheng, C. H., Tsai, M. C., & Chang, Y. S. (2023). The relationship between hotel star rating and website information quality based on visual presentation. PLOS ONE (Vol. 18, No. 11, e0290629).