fiftyone.utils.eval.regression.RegressionResults

class documentation

class RegressionResults(BaseEvaluationResults): (source)

Constructor: RegressionResults(samples, config, eval_key, ytrue, ...)

Class that stores the results of a regression evaluation.

Parameters
samples	the `fiftyone.core.collections.SampleCollection` used
config	the `RegressionEvaluationConfig` used
eval_key	the evaluation key
ytrue	a list of ground truth values
ypred	a list of predicted values
confs	an optional list of confidences for the predictions
eval_key	the evaluation key of the evaluation
gt_field	the name of the ground truth field
pred_field	the name of the predictions field
ids	a list of sample or frame IDs corresponding to the regressions
missing	a missing value. Any None-valued regressions are given this value for results purposes
custom_metrics	an optional dict of custom metrics
backend	a `RegressionEvaluation` backend

Method	`__init__`	Undocumented
Method	`metrics`	Computes various popular regression metrics for the results.
Method	`plot_results`	Plots the regression results.
Method	`print_metrics`	Prints the metrics computed via `metrics`.
Instance Variable	`confs`	Undocumented
Instance Variable	`ids`	Undocumented
Instance Variable	`missing`	Undocumented
Instance Variable	`ypred`	Undocumented
Instance Variable	`ytrue`	Undocumented
Class Method	`_from_dict`	Subclass implementation of `from_dict`.

Inherited from BaseEvaluationResults:

Method	`_get_custom_metrics`	Undocumented
Method	`_print_metrics`	Undocumented

Inherited from BaseRunResults (via BaseEvaluationResults, EvaluationResults):

Class Method	`from_dict`	Builds a `BaseRunResults` from a JSON dict representation of it.
Static Method	`base_results_cls`	Returns the results class for the given run type.
Method	`attributes`	Returns the list of class attributes that will be serialized by `serialize`.
Method	`save`	Saves the results to the database.
Method	`save_config`	Saves these results config to the database.
Property	`cls`	The fully-qualified name of this `BaseRunResults` class.
Property	`config`	The `BaseRunConfig` for these results.
Property	`key`	The run key for these results.
Property	`samples`	The `fiftyone.core.collections.SampleCollection` associated with these results.
Instance Variable	`_backend`	Undocumented
Instance Variable	`_config`	Undocumented
Instance Variable	`_key`	Undocumented
Instance Variable	`_samples`	Undocumented

def __init__(self, samples, config, eval_key, ytrue, ypred, confs=None, ids=None, missing=None, custom_metrics=None, backend=None): (source) ¶

overrides fiftyone.utils.eval.base.BaseEvaluationResults.__init__

Undocumented

def metrics(self, weights=None): (source) ¶

overrides fiftyone.utils.eval.base.BaseEvaluationResults.metrics

Computes various popular regression metrics for the results.

The computed metrics are:

Mean squared error: sklearn:sklearn.metrics.mean_squared_error
Root mean squared error: sklearn:sklearn.metrics.mean_squared_error
Mean absolute error: sklearn:sklearn.metrics.mean_absolute_error
Median absolute error: sklearn:sklearn.metrics.median_absolute_error
R^2 score: sklearn:sklearn.metrics.r2_score
Explained variance score: sklearn:sklearn.metrics.explained_variance_score
Max error: sklearn:sklearn.metrics.max_error
Support: the number of examples

Also includes any custom metrics from custom_metrics.

Parameters
weights:`None`	an optional list of weights for each example
Returns
a dict

def plot_results(self, labels=None, sizes=None, backend='plotly', **kwargs): (source) ¶

Plots the regression results.

You can use the labels parameters to define a coloring for the points, and you can use the sizes parameter to scale the sizes of the points.

You can attach plots generated by this method to an App session via its fiftyone.core.session.Session.plots attribute, which will automatically sync the session's view with the currently selected points in the plot.

Parameters
labels:`None`	data to use to color the points. Can be any of the following: the name of a sample field or `embedded.field.name` of from which to extract numeric or string values a `fiftyone.core.expressions.ViewExpression` defining numeric or string values to extract via `fiftyone.core.collections.SampleCollection.values` a list or array-like of numeric or string values (or lists of lists for frame-level regressions)
sizes:`None`	data to use to scale the sizes of the points. Can be any of the following: the name of a sample field or `embedded.field.name` from which to extract numeric values a `fiftyone.core.expressions.ViewExpression` defining numeric values to extract via `fiftyone.core.collections.SampleCollection.values` a list or array-like of numeric values (or lists of lists for frame-level regressions)
backend:"plotly"	the plotting backend to use. Supported values are `("plotly", "matplotlib")`
**kwargs	keyword arguments for the backend plotting method: "plotly" backend: `fiftyone.core.plots.plotly.plot_regressions` "matplotlib" backend: `fiftyone.core.plots.matplotlib.plot_regressions`
Returns
an `fiftyone.core.plots.base.InteractivePlot`

def print_metrics(self, weights=None, digits=2): (source) ¶

overrides fiftyone.utils.eval.base.BaseEvaluationResults.print_metrics

Prints the metrics computed via metrics.

Parameters
weights:`None`	an optional list of weights for each example
digits:2	the number of digits of precision to print

confs: None = (source) ¶

Undocumented

ids: None = (source) ¶

Undocumented

missing: None = (source) ¶

Undocumented

ypred = (source) ¶

Undocumented

ytrue = (source) ¶

Undocumented

@classmethod
def _from_dict(cls, d, samples, config, eval_key, **kwargs): (source) ¶

overrides fiftyone.core.runs.BaseRunResults._from_dict

Subclass implementation of from_dict.

Parameters
d	a JSON dict
samples	the `fiftyone.core.collections.SampleCollection` for the run
config	the `BaseRunConfig` for the run
eval_key	Undocumented
key	the run key
**kwargs	Undocumented
Returns
a `BaseRunResults`