onion_clustering.onion_uni.ClusterMixin¶
- class onion_clustering.onion_uni.ClusterMixin[source]¶
Mixin class for all cluster estimators in scikit-learn.
_estimator_type class attribute defaulting to “clusterer”;
fit_predict method returning the cluster labels associated to each sample.
Examples
>>> import numpy as np >>> from sklearn.base import BaseEstimator, ClusterMixin >>> class MyClusterer(ClusterMixin, BaseEstimator): ... def fit(self, X, y=None): ... self.labels_ = np.ones(shape=(len(X),), dtype=np.int64) ... return self >>> X = [[1, 2], [2, 3], [3, 4]] >>> MyClusterer().fit_predict(X) array([1, 1, 1])
Methods
Perform clustering on X and returns cluster labels.
- fit_predict(X, y=None, **kwargs)[source]¶
Perform clustering on X and returns cluster labels.
- Parameters:
X (array-like of shape (n_samples, n_features)) – Input data.
y (Ignored) – Not used, present for API consistency by convention.
**kwargs (dict) –
Arguments to be passed to
fit
.Added in version 1.4.
- Returns:
labels – Cluster labels.
- Return type:
ndarray of shape (n_samples,), dtype=np.int64