A Decision Tree of Ignition Point for Simple Inflammable Chemical Compounds

Abstract

Ignition point, the temperature at which a chemical compound begins to burn naturally, is one of the important values from the viewpoint of industry and safety. This manuscript addresses a trial prediction of the ignition point for relatively simple chemical compounds including carbon, oxygen and hydrogen via data mining such as decision tree and random forest. I used fundamental material values and the number of characteristic structures as descriptors for chemical compounds. Our input data file includes 240 kinds of chemical compounds and we prepared other 10 as the test data. At first, I used “rpart” package of the “R”, one of the statistical programming language, in order to process decision tree. Furthermore I used “randomForest” with more data and more number of descriptors and I got better estimation of ignition point.