TSD based framework for mining the induction rules

• The paper presents a natural algorithm which is based on alligator's egg incubation technique.
• Theoretical analysis of proposed algorithm is given based on statistical learning theory.
• Proposed algorithm is also compared with other state of art techniques.
• Testing accuracy of proposed algorithm is worked out for nine datasets.
• ROC analysis and non-parametric test are also conducted.

Sex determination mainly encompasses two aspects: genotypic sex determination (GSD) and temperature-dependent sex determination (TSD). Genotypic sex determination performs its task by observing the presence of sex chromosomes. In many reptiles sex determination is greatly influenced by the environmental conditions such as temperature of the nest, weight and size of eggs. A nature inspired algorithm which mimics the mechanism of temperature dependent sex determination (TSD) has been introduced for mining the classification rules from datasets. A comparison of proposed TSD algorithm with other well known rule induction algorithms like PRISM, C4.5, 1-R, CN2, and NN has been evaluated on some bench mark datasets.