Pugazhendi, D (2013) Apriori algorithm on Marine Fisheries Biological Data. International Journal of Computer Science & Engineering Technology, 4 (12). pp. 1409-1411.
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Abstract
Abstract - Data Mining (DM) is the process of analysing data from different vista and gives summary on specific determination. Association rules are rules describing the associations or correlations to bring out the hidden pattern among attributes in data sets. The most widely used algorithm in association technique is Apriori algorithm which is meant for only categorical data analysis. The sample fishery biological data consist of six attributes out of which two are numerical values. As a new attempt, the numerical values were converted to unique nominal values in order to maintain all categorical values. The Apriori algorithm applied on specific criteria such as minimum support and confidence enabled to derive many meaningful patterns on different perspectives. The taeniopterus apecies has more associations between the attributes of total_length range between 120 to 150 and month of August, weight of Thirty and sex of Male.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Data Mining on Fishery Biology; Association on fishery data; length and weight data; Data Mining; Association |
| Subjects: | Marine Fisheries |
| Divisions: | CMFRI-Madras (Chennai) |
| Depositing User: | Arun Surendran |
| Date Deposited: | 08 Jan 2014 05:44 |
| Last Modified: | 09 Sep 2015 15:57 |
| URI: | http://eprints.cmfri.org.in/id/eprint/9743 |
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