Class: 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.
Constructors
new DetCurveDisplay()
new DetCurveDisplay(
opts?):DetCurveDisplay
Parameters
| Parameter | 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 | boolean | The label of the positive class. |
Returns DetCurveDisplay
Defined in generated/metrics/DetCurveDisplay.ts:25
Properties
| Property | Type | Default value | Defined in |
|---|---|---|---|
_isDisposed | boolean | false | generated/metrics/DetCurveDisplay.ts:23 |
_isInitialized | boolean | false | generated/metrics/DetCurveDisplay.ts:22 |
_py | PythonBridge | undefined | generated/metrics/DetCurveDisplay.ts:21 |
id | string | undefined | generated/metrics/DetCurveDisplay.ts:18 |
opts | any | undefined | generated/metrics/DetCurveDisplay.ts:19 |
Accessors
ax_
Get Signature
get ax_():
Promise<any>
Axes with DET Curve.
Returns Promise<any>
Defined in generated/metrics/DetCurveDisplay.ts:326
figure_
Get Signature
get figure_():
Promise<any>
Figure containing the curve.
Returns Promise<any>
Defined in generated/metrics/DetCurveDisplay.ts:349
line_
Get Signature
get line_():
Promise<any>
DET Curve.
Returns Promise<any>
Defined in generated/metrics/DetCurveDisplay.ts:303
py
Get Signature
get py():
PythonBridge
Returns PythonBridge
Set Signature
set py(
pythonBridge):void
Parameters
| Parameter | Type |
|---|---|
pythonBridge | PythonBridge |
Returns void
Defined in generated/metrics/DetCurveDisplay.ts:50
Methods
dispose()
dispose():
Promise<void>
Disposes of the underlying Python resources.
Once dispose() is called, the instance is no longer usable.
Returns Promise<void>
Defined in generated/metrics/DetCurveDisplay.ts:102
from_estimator()
from_estimator(
opts):Promise<any>
Plot DET curve given an estimator and data.
Read more in the User Guide.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
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 | boolean | 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.X? | ArrayLike | Input values. |
opts.y? | ArrayLike | Target values. |
Returns Promise<any>
Defined in generated/metrics/DetCurveDisplay.ts:121
from_predictions()
from_predictions(
opts):Promise<any>
Plot the DET curve given the true and predicted labels.
Read more in the User Guide.
Parameters
| Parameter | 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 | boolean | 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:197
init()
init(
py):Promise<void>
Initializes the underlying Python resources.
This instance is not usable until the Promise returned by init() resolves.
Parameters
| Parameter | Type |
|---|---|
py | PythonBridge |
Returns Promise<void>
Defined in generated/metrics/DetCurveDisplay.ts:63
plot()
plot(
opts):Promise<any>
Plot visualization.
Parameters
| Parameter | 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:261