  In this paper, naive Bayesian and C4.5 Decision Tree Classifiers(DTC) are
successively applied on materials informatics to classify the engineering
materials into different classes for the selection of materials that suit the
input design specifications. Here, the classifiers are analyzed individually
and their performance evaluation is analyzed with confusion matrix predictive
parameters and standard measures, the classification results are analyzed on
different class of materials. Comparison of classifiers has found that naive
Bayesian classifier is more accurate and better than the C4.5 DTC. The
knowledge discovered by the naive bayesian classifier can be employed for
decision making in materials selection in manufacturing industries.
