class_docstr: An abstract base class for a model for which data consists of a
  features matrix and a labels vector, namely for (one-class
  supervised learning)
  
  Attributes
  ----------
  features : `numpy.ndarray`, shape=(n_samples, n_features) (read-only)
      The features matrix
  
  labels : `numpy.ndarray`, shape=(n_samples,)  (read-only)
      The labels vector
  
  n_samples : `int`  (read-only)
      Number of samples
  
  n_features : `int` (read-only)
      Number of features
  
  dtype : `{'float64', 'float32'}`
      Type of the data arrays used.
  
  Notes
  -----
  This class should be not used by end-users, it is intended for
  development only.
code: def __init__(self):
      Model.__init__(self)
      self.features = None
      self.labels = None
      self.n_features = None
      self.n_samples = None
  
file_path: tick/tick/base_model/model_labels_features.py
imports: import numpy
  from .None import Model
  from tick.preprocessing.utils import safe_array
label_desc: Use image node_id 1 to create a new ModelLabelsFeatures object from inherited base classes: Model with example: obj = ModelLabelsFeatures()