Class: RadiusNeighborsClassifier
Classifier implementing a vote among neighbors within a given radius.
Read more in the User Guide.
Constructors
new RadiusNeighborsClassifier()
new RadiusNeighborsClassifier(
opts?):RadiusNeighborsClassifier
Parameters
| Parameter | Type | Description |
|---|---|---|
opts? | object | - |
opts.algorithm? | "auto" | "ball_tree" | "kd_tree" | "brute" | Algorithm used to compute the nearest neighbors: |
opts.leaf_size? | number | Leaf size passed to BallTree or KDTree. This can affect the speed of the construction and query, as well as the memory required to store the tree. The optimal value depends on the nature of the problem. |
opts.metric? | string | Metric to use for distance computation. Default is “minkowski”, which results in the standard Euclidean distance when p = 2. See the documentation of scipy.spatial.distance and the metrics listed in distance_metrics for valid metric values. If metric is “precomputed”, X is assumed to be a distance matrix and must be square during fit. X may be a sparse graph, in which case only “nonzero” elements may be considered neighbors. If metric is a callable function, it takes two arrays representing 1D vectors as inputs and must return one value indicating the distance between those vectors. This works for Scipy’s metrics, but is less efficient than passing the metric name as a string. |
opts.metric_params? | any | Additional keyword arguments for the metric function. |
opts.n_jobs? | number | The number of parallel jobs to run for neighbors search. undefined means 1 unless in a joblib.parallel_backend context. \-1 means using all processors. See Glossary for more details. |
opts.outlier_label? | "most_frequent" | Label for outlier samples (samples with no neighbors in given radius). |
opts.p? | number | Power parameter for the Minkowski metric. When p = 1, this is equivalent to using manhattan_distance (l1), and euclidean_distance (l2) for p = 2. For arbitrary p, minkowski_distance (l_p) is used. This parameter is expected to be positive. |
opts.radius? | number | Range of parameter space to use by default for radius_neighbors queries. |
opts.weights? | "uniform" | "distance" | Weight function used in prediction. Possible values: |
Returns RadiusNeighborsClassifier
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:23
Properties
| Property | Type | Default value | Defined in |
|---|---|---|---|
_isDisposed | boolean | false | generated/neighbors/RadiusNeighborsClassifier.ts:21 |
_isInitialized | boolean | false | generated/neighbors/RadiusNeighborsClassifier.ts:20 |
_py | PythonBridge | undefined | generated/neighbors/RadiusNeighborsClassifier.ts:19 |
id | string | undefined | generated/neighbors/RadiusNeighborsClassifier.ts:16 |
opts | any | undefined | generated/neighbors/RadiusNeighborsClassifier.ts:17 |
Accessors
classes_
Get Signature
get classes_():
Promise<ArrayLike>
Class labels known to the classifier.
Returns Promise<ArrayLike>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:515
effective_metric_
Get Signature
get effective_metric_():
Promise<string>
The distance metric used. It will be same as the metric parameter or a synonym of it, e.g. ‘euclidean’ if the metric parameter set to ‘minkowski’ and p parameter set to 2.
Returns Promise<string>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:542
effective_metric_params_
Get Signature
get effective_metric_params_():
Promise<any>
Additional keyword arguments for the metric function. For most metrics will be same with metric_params parameter, but may also contain the p parameter value if the effective_metric_ attribute is set to ‘minkowski’.
Returns Promise<any>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:569
feature_names_in_
Get Signature
get feature_names_in_():
Promise<ArrayLike>
Names of features seen during fit. Defined only when X has feature names that are all strings.
Returns Promise<ArrayLike>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:623
n_features_in_
Get Signature
get n_features_in_():
Promise<number>
Number of features seen during fit.
Returns Promise<number>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:596
n_samples_fit_
Get Signature
get n_samples_fit_():
Promise<number>
Number of samples in the fitted data.
Returns Promise<number>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:650
outlier_label_
Get Signature
get outlier_label_():
Promise<number|ArrayLike>
Label which is given for outlier samples (samples with no neighbors on given radius).
Returns Promise<number | ArrayLike>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:677
outputs_2d_
Get Signature
get outputs_2d_():
Promise<boolean>
False when y’s shape is (n_samples, ) or (n_samples, 1) during fit otherwise true.
Returns Promise<boolean>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:704
py
Get Signature
get py():
PythonBridge
Returns PythonBridge
Set Signature
set py(
pythonBridge):void
Parameters
| Parameter | Type |
|---|---|
pythonBridge | PythonBridge |
Returns void
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:89
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/neighbors/RadiusNeighborsClassifier.ts:145
fit()
fit(
opts):Promise<any>
Fit the radius neighbors classifier from the training dataset.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | ArrayLike | Training data. |
opts.y? | any | Target values. |
Returns Promise<any>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:162
get_metadata_routing()
get_metadata_routing(
opts):Promise<any>
Get metadata routing of this object.
Please check User Guide on how the routing mechanism works.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.routing? | any | A MetadataRequest encapsulating routing information. |
Returns Promise<any>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:203
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/neighbors/RadiusNeighborsClassifier.ts:102
predict()
predict(
opts):Promise<ArrayLike>
Predict the class labels for the provided data.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | any | Test samples. |
Returns Promise<ArrayLike>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:239
predict_proba()
predict_proba(
opts):Promise<any>
Return probability estimates for the test data X.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.X? | any | Test samples. |
Returns Promise<any>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:275
radius_neighbors()
radius_neighbors(
opts):Promise<any>
Find the neighbors within a given radius of a point or points.
Return the indices and distances of each point from the dataset lying in a ball with size radius around the points of the query array. Points lying on the boundary are included in the results.
The result points are not necessarily sorted by distance to their query point.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.radius? | number | Limiting distance of neighbors to return. The default is the value passed to the constructor. |
opts.return_distance? | boolean | Whether or not to return the distances. |
opts.sort_results? | boolean | If true, the distances and indices will be sorted by increasing distances before being returned. If false, the results may not be sorted. If return_distance=False, setting sort_results=True will result in an error. |
opts.X? | any | The query point or points. If not provided, neighbors of each indexed point are returned. In this case, the query point is not considered its own neighbor. |
Returns Promise<any>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:315
radius_neighbors_graph()
radius_neighbors_graph(
opts):Promise<any[]>
Compute the (weighted) graph of Neighbors for points in X.
Neighborhoods are restricted the points at a distance lower than radius.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.mode? | "connectivity" | "distance" | Type of returned matrix: ‘connectivity’ will return the connectivity matrix with ones and zeros, in ‘distance’ the edges are distances between points, type of distance depends on the selected metric parameter in NearestNeighbors class. |
opts.radius? | number | Radius of neighborhoods. The default is the value passed to the constructor. |
opts.sort_results? | boolean | If true, in each row of the result, the non-zero entries will be sorted by increasing distances. If false, the non-zero entries may not be sorted. Only used with mode=’distance’. |
opts.X? | ArrayLike | The query point or points. If not provided, neighbors of each indexed point are returned. In this case, the query point is not considered its own neighbor. |
Returns Promise<any[]>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:372
score()
score(
opts):Promise<number>
Return the mean accuracy on the given test data and labels.
In multi-label classification, this is the subset accuracy which is a harsh metric since you require for each sample that each label set be correctly predicted.
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.sample_weight? | ArrayLike | Sample weights. |
opts.X? | ArrayLike[] | Test samples. |
opts.y? | ArrayLike | True labels for X. |
Returns Promise<number>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:429
set_score_request()
set_score_request(
opts):Promise<any>
Request metadata passed to the score method.
Note that this method is only relevant if enable_metadata_routing=True (see sklearn.set_config). Please see User Guide on how the routing mechanism works.
The options for each parameter are:
Parameters
| Parameter | Type | Description |
|---|---|---|
opts | object | - |
opts.sample_weight? | string | boolean | Metadata routing for sample_weight parameter in score. |
Returns Promise<any>
Defined in generated/neighbors/RadiusNeighborsClassifier.ts:479