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Lasso+L0 performed on a tailor made feature space was introduced in [Phys. Rev. Lett. 114, 105503 (2015)](http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.114.105503).
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The application of the method goes through these step:
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* The *feature space* is generated by creating a list of analytical expressions (the *derived features*), obtained by combining the selected *primary features* and operations.
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* The Least Absolute Shrinkage and Selection Operator ([LASSO](http://statweb.stanford.edu/~tibs/lasso.html)) is applied. In practice the following minimization is performed:
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[LASSOformula](/uploads/d9ec2dffb0f29594532cb4f7994f40d1/LASSOformula)
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where **P** is a vector listing the property of interest (here, the RS - ZB difference in energy) for all data points (here, binary materials), **D** is a matrix whose columns are the *derived features* listed for each material, **c** is the (sparse) vector of coefficients that is found upon minimization.
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A short summary of the method will appear below soon.
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[Back to analytics wiki home](./Home) |
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