Decision Tree using Application of Machine Learning

7 Decision Tree using Application of Machine Learning 

As the entire tree is complex and cannot be clearly displayed in one screen, we report in Fig. 4-17 an expanded (zoomed) fraction of the nonaromatic population set of the tree. 

Since this current study is restricted to the best enantioseparations (a 1.8), it is quite clear that the tree does not accurately reflect the full information contained in CHIRBASE. 

However, it has provided some interesting results. At the top of the tree, the molecule population is first divided according to the presence or absence of the attribute NH2 (primary amine). If the answer is yes , the developed branches (on the right of the tree) mostly leads to the Crownpak CSP. The next attribute is Aromatic . If the answer is no , here the predominant CSP is Chiralpak AD. Aromatic compounds form the largest part of the tree and as expected the dominant CSP is Chiralcel OD which is disseminated in almost every region of the tree. 

4 CHIRBASE Database Current Status and Derived Research Applications using. .. 

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