sf.apps.data.feature.QM9MC¶
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class
QM9MC
[source]¶ Bases:
strawberryfields.apps.data.feature.FeatureDataset
Monte-Carlo estimated feature vectors of 1100 randomly-chosen molecules from the QM9 dataset.
The QM9 dataset is widely used in benchmarking performance of machine learning models in estimating molecular properties [7], [8].
Coulomb matrices were used as adjacency matrices to represent molecules in this case.
The exactly-calculated feature vectors of certain orbits of these 1100 molecules are also available in the
QM9Exact
class.-
method = "mc"
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n_mean = 6
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unit = "events"
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unit_data = [[2, 2], [4, 2], [6, 2]]
Attributes
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code/api/api/strawberryfields.apps.data.feature.QM9MC
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