class_docstr: An unsupervised machine learning algorithm to reduce feature dimensionality.
  
  As a result, number of features within a dataset is reduced but the dataset still
  retain as much information as possible.
docstr: Return a :class:`~sagemaker.amazon.pca.PCAModel`.
  
  It references the latest s3 model data produced by this Estimator.
  
  Args:
      vpc_config_override (dict[str, list[str]]): Optional override for VpcConfig set on
          the model. Default: use subnets and security groups from this Estimator.
          * 'Subnets' (list[str]): List of subnet ids.
          * 'SecurityGroupIds' (list[str]): List of security group ids.
      **kwargs: Additional kwargs passed to the PCAModel constructor.
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code: def create_model(
      self, vpc_config_override=VPC_CONFIG_DEFAULT, **kwargs
  ):
      """Return a :class:`~sagemaker.amazon.pca.PCAModel`.
  
      It references the latest s3 model data produced by this Estimator.
  
      Args:
          vpc_config_override (dict[str, list[str]]): Optional override for VpcConfig set on
              the model. Default: use subnets and security groups from this Estimator.
              * 'Subnets' (list[str]): List of subnet ids.
              * 'SecurityGroupIds' (list[str]): List of security group ids.
          **kwargs: Additional kwargs passed to the PCAModel constructor.
      """
      return PCAModel(
          self.model_data,
          self.role,
          sagemaker_session=self.sagemaker_session,
          vpc_config=self.get_vpc_config(vpc_config_override),
          **kwargs,
      )
  
imports: from __future__ import absolute_import
  from typing import Union, Optional
  from sagemaker import image_uris
  from sagemaker.amazon.amazon_estimator import AmazonAlgorithmEstimatorBase
  from sagemaker.amazon.common import RecordSerializer, RecordDeserializer
  from sagemaker.amazon.hyperparameter import Hyperparameter
  from sagemaker.amazon.validation import gt, isin
  from sagemaker.predictor import Predictor
  from sagemaker.model import Model
  from sagemaker.session import Session
  from sagemaker.utils import pop_out_unused_kwarg
  from sagemaker.vpc_utils import VPC_CONFIG_DEFAULT
  from sagemaker.workflow.entities import PipelineVariable
label_desc: Use image node_id 2 for calling the PCA obj's underlying member method code with example usage: obj.create_model(vpc_config_override) and returns: PCAModel