Evaluating the robustness of goodness-of-fit measures for hierarchical clustering

Timofeeva, Anastasiia

doi:10.1088/1742-6596/1145/1/012049

Cited by 3 publications

(1 citation statement)

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“…A widely used cluster validity index, the cophenetic correlation coefficient (CCC), was used to assess the efficiency of the dendrogram. CCC computes the correlation between the actual dissimilarity matrix and computed dissimilarity matrix [40]. It is represented by a cophenetic matrix (CM) generated after the HCA algorithm re-computes the (dis)similarities [21].…”

Section: B Students' Performance Predictive Analyticsmentioning

confidence: 99%

A Framework for Software Defect Prediction Using Feature Selection and Ensemble Learning Techniques

Matloob¹,

Aftab²,

Iqbal³

2019

IJMECS

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Persistent and quality graduation rates of students are increasingly important indicators of progressive and effective educational institutions. Timely analysis of students' data to guide instructors in the provision of academic interventions to students who are at risk of performing poorly in their courses or dropout is vital for academic achievement. In addition there is need for performance attributes relationship mining for the generation of comprehensible patterns. However, there is dearth in pieces of knowledge relating to predicting students' performance from patterns. This therefore paper adopts hierarchical cluster analysis (HCA) to analyze students' performance dataset for the discovery of optimal number of fail courses clusters and partitioning of the courses into groups, and association rule mining for the extraction of interesting course-status association. Agglomerative HCA with Ward's linkage method produced the best clustering structure (five clusters) with a coefficient of 92% and silhouette width 0.57. Apriori algorithm with support (0.5%), confidence (80%) and lift (1) thresholds were used in the extraction of rules with student's status as consequent. Out of the twenty one courses offered by students in the first year, seven courses frequently occur together as failed courses, and their impact on the respective students' performance status were assessed in the rules. It is conjectured that early intervention by the instructors and management of educational activities on these seven courses will increase the students' learning outcomes leading to increased graduation rate at minimum course duration, which is the overarching objective of higher educational institutions.

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Section: B Students' Performance Predictive Analyticsmentioning

confidence: 99%