Training Data for Decision Tree Practical in reading-ml-chemistry repo

This is a dataset that can be used to train a decision tree to predict the band gap of a material. The data is associated with a notebook for running the practical and it can be found at https://github.com/keeeto/reading-ml-chemistry. The data originally comes from the Materials Project. A new muon spectroscopy dataset is added. It is from - Machine learning approach to muon spectroscopy analysis - https://iopscience.iop.org/article/10.1088/1361-648X/abe39e/meta

Keywords

Pharmacology, Materials Project, Chemical Sciences not elsewhere classified, Science Policy, Information Systems not elsewhere classified, Decision Tree, Biochemistry, Microbiology, Inorganic Chemistry, training Data, http, band gap, data, reading-ml-chemistry repo, material, Environmental Sciences not elsewhere classified, dataset, Cancer, Biological Sciences not elsewhere classified, nbsp

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