… The performance of the proposed model can be measured by using the accuracy, precision,
recall, and error value metrics of machine learning approaches. From the four approaches, …

… To ensure that their performance is due to learning from their training set only, we disallowed
peer discussion and internet use. To incentivise both performance and completion, they …

… By using these algorithms, teachers could build customized curriculums for students who
have different learning abilities. Another study on ML in evaluation of educational techniques …

… can be proposed to evaluate the accuracy of classification … to evaluate the various
performance evaluation metrics. … ) are used in this analysis, the performance needs to be proved …

… performance degradation. To overcome this issue, this work aims at the evaluation of the
performance of different machine learning … show the performance of different machine learning …

… learning evaluations, we use internal validity to refer to validity properties within a learning
… This goes beyond test set performance on an individual learning problem and is anchored …

… employ exploratory factor analysis (EFA), confirmatory factor analysis (CFA) … performance.
It is believed that COVID-19 has a profound influence on the educational system's performance…

… cases, the evaluation of learners’ performance in intelligent … for refining the evaluation of
students’ performance using fuzzy … and objectivity in the evaluation of students’ performance. …

… and disappointments regarding true performance in real-life … on how to assess performance
reliably and efficiently and … both the most relevant performance evaluation criteria as well as …

… The paper [9] described different clustering algorithms for predication on BUPA liver disorder
and ILPD dataset for performance analysis. The simple BIZ model was selected effectively. …