Code Documentation: Metrics¶
mastml.metrics Module¶
This module contains a metrics class for construction and evaluation of various regression score metrics between true and model predicted data.
- Metrics:
Class to construct and evaluate a list of regression metrics of interest. The full list of available metrics can be obtained from Metrics()._metric_zoo()
Functions¶
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Method that calculates the adjusted R^2 value |
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Method that calculates the R^2 value |
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Method that calculates the R^2 value without fitting the y-intercept |
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Method that calculates the root mean squared error (RMSE) of a set of data, divided by the standard deviation of the training data set. |
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Method that calculates the root mean squared error (RMSE) |
Classes¶
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Ordinary least squares Linear Regression. |
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Class containing access to a wide range of metrics from scikit-learn and a number of MAST-ML custom-written metrics |