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Ponte Academic Journal
Oct 2017, Volume 73, Issue 10

EVALUATION OF STUDENT PERFORMANCE USING AN OUTLIER DETECTION APPROACH

Author(s): V.V.JAYA RAMA KRISHNAIAH ,PENUBOTHU AJITH, KURRA RAJASEKHARA RAO

J. Ponte - Oct 2017 - Volume 73 - Issue 10
doi: 10.21506/j.ponte.2017.10.7



Abstract:
The major objective of the Data Mining Techniques is to extract the valuable information from the valid repositories. The Knowledge Detection plays a vital role in the Education Domain in terms of finding useful information about the students based on their learning process. During KDD process, the data is collected from various kinds of sources with different nature properties. A good decision is always influenced by the factors like collection patterns, quires and other related factors like Outliers. In this paper, we worked on detection of outliers, which plays n vital role in decision making. We analysed the performance of the students and present the results using outlier detection process. The abstracted results are analysed and presented using graphical methods like Histograms and pie charts.
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