Enhancement of fraternal K-median algorithm with CNN for high dropout probabilities to evolve optimal time-complexity

Nagaraj, B.; Rajendran, Arunkumar; Nisi, K.; Vijayakumar, P.

doi:10.1007/s10586-019-02963-9

Cited by 3 publications

(1 citation statement)

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“…The clustering procedure based on K-means algorithm includes initialization, computation of cluster centers, distance calculation, guideline of the termination circumstance and computation of the target function. Nagaraj et al (2019) used fraternal K-median clustering algorithm as the preprocessing schemes. The research applied dropout regularization mechanism to improve the precision by letting network over fit decision of CNN.…”

Section: Literature Reviewmentioning

confidence: 99%

Students' Academic Performance Analysis by K-Means Clustering for Investigating Students' Health Conditions within Clusters

Goh¹,

Goh²,

Yip³

et al. 2020

ATMPH

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Schooling systems always offer finest teaching and learning opportunities to reach the educational requirements and ensuring achievement for every student. However, health affects students' academic performance directly. All teachers monitor their students' progress throughout the year, includes formative assessment, attendance rates, involvement in the organization, etc. This practice helps teachers continually assess the conditions of students and their academic performance. Data mining is a process to explore certain style and hidden correlation among massive volume of data. Data mining is applied in multiple disciplinary fields, for example, insurance, education, banking and bioinformatics. Data mining skills such as clustering, classification, regression and prediction are commonly used by educators to measure academic performance. In this paper, method of k-means clustering with deterministic model is applied to analyze the student's overall performance. The students' assessment scores are assigned to k clusters without prior knowledge of the scores. The result is important for educators to further investigate the effect of sickness of students within a cluster that may lead to poor academic performance.

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Section: Literature Reviewmentioning

confidence: 99%