class_docstr: Multilabel confusion matrix class.
  
  >>> mlcm = MultiLabelCM([{'dog'}, {'cat', 'dog'}], [{'cat'}, {'cat'}])
  >>> mlcm.actual_vector_multihot
  [[0, 1], [1, 1]]
  >>> mlcm.predict_vector_multihot
  [[1, 0], [1, 0]]
docstr: Init method.
  
  :param actual_vector: actual vector
  :type actual_vector: python list or numpy array of sets
  :param predict_vector: vector of predictions
  :type predict_vector: python list or numpy array of sets
  :param sample_weight: sample weights list
  :type sample_weight: python list or numpy array
  :param classes: ordered labels of classes
  :type classes: list
docstr_tok: ["Init","method",".",":","param","actual_vector",":","actual","vector",":","type","actual_vector",":","python","list","or","numpy","array","of","sets",":","param","predict_vector",":","vector","of","predictions",":","type","predict_vector",":","python","list","or","numpy","array","of","sets",":","param","sample_weight",":","sample","weights","list",":","type","sample_weight",":","python","list","or","numpy","array",":","param","classes",":","ordered","labels","of","classes",":","type","classes",":","list"]
code: def __init__(
      self,
      actual_vector,
      predict_vector,
      sample_weight=None,
      classes=None,
  ):
      """
      Init method.
  
      :param actual_vector: actual vector
      :type actual_vector: python list or numpy array of sets
      :param predict_vector: vector of predictions
      :type predict_vector: python list or numpy array of sets
      :param sample_weight: sample weights list
      :type sample_weight: python list or numpy array
      :param classes: ordered labels of classes
      :type classes: list
      """
      self.actual_vector = actual_vector
      self.actual_vector_multihot = []
      self.predict_vector = predict_vector
      self.predict_vector_multihot = []
      self.weights = None
      self.classes = None
      self.classwise_cms = {}
      self.samplewise_cms = {}
      __mlcm_vector_handler__(
          self, actual_vector, predict_vector, sample_weight, classes
      )
      __mlcm_assign_classes__(self, classes)
      __mlcm_vectors_filter__(self)
  
file_path: pycm/pycm/pycm_multilabel_cm.py
imports: from __future__ import division
  from .pycm_error import pycmVectorError, pycmMultiLabelError
  from .pycm_param import *
  from .pycm_obj import ConfusionMatrix
  import numpy
label_desc: Use image node_id 1 to create a new MultiLabelCM object  with example: obj = MultiLabelCM(actual_vector, predict_vector, sample_weight, classes)