R2Score#
- class ignite.contrib.metrics.regression.R2Score(output_transform=<function Metric.<lambda>>, device=device(type='cpu'))[source]#
Calculates the R-Squared, the coefficient of determination.
$R^2 = 1 - \frac{\sum_{j=1}^n(A_j - P_j)^2}{\sum_{j=1}^n(A_j - \bar{A})^2}$where $A_j$ is the ground truth, $P_j$ is the predicted value and $\bar{A}$ is the mean of the ground truth.
update
must receive output of the form(y_pred, y)
or{'y_pred': y_pred, 'y': y}
.y and y_pred must be of same shape (N, ) or (N, 1) and of type float32.
Parameters are inherited from
Metric.__init__
.- Parameters
output_transform (Callable) – a callable that is used to transform the
Engine
’sprocess_function
’s output into the form expected by the metric. This can be useful if, for example, you have a multi-output model and you want to compute the metric with respect to one of the outputs. By default, metrics require the output as(y_pred, y)
or{'y_pred': y_pred, 'y': y}
.device (Union[str, device]) – specifies which device updates are accumulated on. Setting the metric’s device to be the same as your
update
arguments ensures theupdate
method is non-blocking. By default, CPU.
Changed in version 0.4.3: Works with DDP.
Methods
Computes the metric based on it's accumulated state.
Resets the metric to it's initial state.
- compute()[source]#
Computes the metric based on it’s accumulated state.
By default, this is called at the end of each epoch.
- Returns
- the actual quantity of interest. However, if a
Mapping
is returned, it will be (shallow) flattened into engine.state.metrics whencompleted()
is called. - Return type
Any
- Raises
NotComputableError – raised when the metric cannot be computed.