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qzhu2017 / PyXtal_ml

a Python3 library for ML modeling materials properties
MIT License
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[FYI] Pie Chart #32

Closed yanxon closed 5 years ago

yanxon commented 5 years ago

The way the Jarvis paper got their pie chart is taking absolute percentage of MAE with ALL descriptors as the reference: (All-Chem)/Chem ~ 42% ---> Chem (All-(Chem+RDF))/(Chem+RDF) ~ 18% ---> RDF

With this data right here created by Dr. Zhu and I, we can clearly see that adding Charge actually makes the performance to drop. MAE of Chem is 0.2197 and MAE of (Chem+Charge) is 0.2226.

Descriptors                       r2            mae     mae diff(%)
Chem+RDF+ADF+Charge+Voronoi       0.9257    0.2023  0
Chem+RDF+ADF+Charge               0.9161    0.2217  9.58971824
Chem+ADF+Charge                   0.9144    0.223   10.23232823
Chem+Charge                       0.9136    0.2226  10.03460208
Chem                              0.9153    0.2197  8.601087494