Abstract

Abalones are sea snails or molluscs otherwise commonly called as ear shells or sea ears. Because of the economic importance of the age of the abalone and the cumbersome process that is involved in calculating it, much research has been done to solve the problem of abalone age prediction using its physical measurements available in the UCI dataset. This paper reviews the various methods like decision trees, clustering, SVM using Tomek links, CGANs and CasCor used in an attempt to solve it. Furthermore, in contrast to previous research that saw this as a classification problem, this paper approaches it as a linear regression problem and analyses the results.

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