DetCurveDisplay
DET curve visualization.
It is recommend to use from\_estimator
or from\_predictions
to create a visualizer. All parameters are stored as attributes.
Read more in the User Guide.
Python Reference (opens in a new tab)
Constructors
constructor()
Signature
new DetCurveDisplay(opts?: object): DetCurveDisplay;
Parameters
Name | Type | Description |
---|---|---|
opts? | object | - |
opts.estimator_name? | string | Name of estimator. If undefined , the estimator name is not shown. |
opts.fnr? | ArrayLike | False negative rate. |
opts.fpr? | ArrayLike | False positive rate. |
opts.pos_label? | string | number | The label of the positive class. |
Returns
Defined in: generated/metrics/DetCurveDisplay.ts:25 (opens in a new tab)
Properties
_isDisposed
boolean
=false
Defined in: generated/metrics/DetCurveDisplay.ts:23 (opens in a new tab)
_isInitialized
boolean
=false
Defined in: generated/metrics/DetCurveDisplay.ts:22 (opens in a new tab)
_py
PythonBridge
Defined in: generated/metrics/DetCurveDisplay.ts:21 (opens in a new tab)
id
string
Defined in: generated/metrics/DetCurveDisplay.ts:18 (opens in a new tab)
opts
any
Defined in: generated/metrics/DetCurveDisplay.ts:19 (opens in a new tab)
Accessors
ax_
Axes with DET Curve.
Signature
ax_(): Promise<any>;
Returns
Promise
<any
>
Defined in: generated/metrics/DetCurveDisplay.ts:361 (opens in a new tab)
figure_
Figure containing the curve.
Signature
figure_(): Promise<any>;
Returns
Promise
<any
>
Defined in: generated/metrics/DetCurveDisplay.ts:384 (opens in a new tab)
line_
DET Curve.
Signature
line_(): Promise<any>;
Returns
Promise
<any
>
Defined in: generated/metrics/DetCurveDisplay.ts:338 (opens in a new tab)
py
Signature
py(): PythonBridge;
Returns
PythonBridge
Defined in: generated/metrics/DetCurveDisplay.ts:50 (opens in a new tab)
Signature
py(pythonBridge: PythonBridge): void;
Parameters
Name | Type |
---|---|
pythonBridge | PythonBridge |
Returns
void
Defined in: generated/metrics/DetCurveDisplay.ts:54 (opens in a new tab)
Methods
dispose()
Disposes of the underlying Python resources.
Once dispose()
is called, the instance is no longer usable.
Signature
dispose(): Promise<void>;
Returns
Promise
<void
>
Defined in: generated/metrics/DetCurveDisplay.ts:107 (opens in a new tab)
from_estimator()
Plot DET curve given an estimator and data.
Read more in the User Guide.
Signature
from_estimator(opts: object): Promise<any>;
Parameters
Name | Type | Description |
---|---|---|
opts | object | - |
opts.X? | ArrayLike | Input values. |
opts.ax? | any | Axes object to plot on. If undefined , a new figure and axes is created. |
opts.estimator? | any | Fitted classifier or a fitted Pipeline in which the last estimator is a classifier. |
opts.kwargs? | any | Additional keywords arguments passed to matplotlib plot function. |
opts.name? | string | Name of DET curve for labeling. If undefined , use the name of the estimator. |
opts.pos_label? | string | number | The label of the positive class. When pos\_label=None , if y\_true is in {-1, 1} or {0, 1}, pos\_label is set to 1, otherwise an error will be raised. |
opts.response_method? | "decision_function" | "auto’} default=’auto" | Specifies whether to use predict_proba or decision_function as the predicted target response. If set to ‘auto’, predict_proba is tried first and if it does not exist decision_function is tried next. |
opts.sample_weight? | ArrayLike | Sample weights. |
opts.y? | ArrayLike | Target values. |
Returns
Promise
<any
>
Defined in: generated/metrics/DetCurveDisplay.ts:126 (opens in a new tab)
from_predictions()
Plot the DET curve given the true and predicted labels.
Read more in the User Guide.
Signature
from_predictions(opts: object): Promise<any>;
Parameters
Name | Type | Description |
---|---|---|
opts | object | - |
opts.ax? | any | Axes object to plot on. If undefined , a new figure and axes is created. |
opts.kwargs? | any | Additional keywords arguments passed to matplotlib plot function. |
opts.name? | string | Name of DET curve for labeling. If undefined , name will be set to "Classifier" . |
opts.pos_label? | string | number | The label of the positive class. When pos\_label=None , if y\_true is in {-1, 1} or {0, 1}, pos\_label is set to 1, otherwise an error will be raised. |
opts.sample_weight? | ArrayLike | Sample weights. |
opts.y_pred? | ArrayLike | Target scores, can either be probability estimates of the positive class, confidence values, or non-thresholded measure of decisions (as returned by decision\_function on some classifiers). |
opts.y_true? | ArrayLike | True labels. |
Returns
Promise
<any
>
Defined in: generated/metrics/DetCurveDisplay.ts:217 (opens in a new tab)
init()
Initializes the underlying Python resources.
This instance is not usable until the Promise
returned by init()
resolves.
Signature
init(py: PythonBridge): Promise<void>;
Parameters
Name | Type |
---|---|
py | PythonBridge |
Returns
Promise
<void
>
Defined in: generated/metrics/DetCurveDisplay.ts:63 (opens in a new tab)
plot()
Plot visualization.
Signature
plot(opts: object): Promise<any>;
Parameters
Name | Type | Description |
---|---|---|
opts | object | - |
opts.ax? | any | Axes object to plot on. If undefined , a new figure and axes is created. |
opts.kwargs? | any | Additional keywords arguments passed to matplotlib plot function. |
opts.name? | string | Name of DET curve for labeling. If undefined , use estimator\_name if it is not undefined , otherwise no labeling is shown. |
Returns
Promise
<any
>
Defined in: generated/metrics/DetCurveDisplay.ts:293 (opens in a new tab)