pyvtna.metrics

Functions

adj_r2(model, data[, k])	Compute the adjusted squared correlation coefficient for predicted values against data
mean_abs_diff(model, data)	Compute the normalized sum of the absolute differences between predicted values against data
pear_r(model, data)	Compute the Pearson Correlation Coefficient predicted values against data
r2(model, data)	Compute the squared correlation coefficient for predicted values against data.
rmsd(model, data)	Compute the root mean squared deviation between predicted values against data

Classes

AdjR2([max_is_best])
MAD([max_is_best])
OverlapMetric([max_is_best])
PearR([max_is_best])
R2([max_is_best])
RMSD([max_is_best])