class_docstr: Density estimation based on Gaussian Mixture Model.
  
  Args:
      n_components (int): Number of components used in the GMM.
docstr: Normalize distance predictions.
  
  Args:
      distances (Tensor): Distance tensor produced by KNN search.
  Returns:
      Tensor: Normalized distances.
code: def _normalize(self, density: Tensor):
      """Normalize distance predictions.
  
      Args:
          distances (Tensor): Distance tensor produced by KNN search.
      Returns:
          Tensor: Normalized distances.
      """
      return (density - self.normalization_statistics.min) / (
          self.normalization_statistics.max
          - self.normalization_statistics.min
      )
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Any
  import torch
  from sklearn.mixture import GaussianMixture
  from torch import Tensor, nn
  from anomalib.models.ai_vad.features import FeatureType
  from anomalib.utils.metrics.min_max import MinMax
label_desc: Use image node_id 6 for calling the GMMEstimator obj's underlying member method code with example usage: obj._normalize(density) and returns: unknown