code: def get_properties(dataset_properties=None):
      data_type = UNSIGNED_DATA
      if dataset_properties is not None:
          signed = dataset_properties.get("signed")
          if signed is not None:
              data_type = (
                  SIGNED_DATA if signed is True else UNSIGNED_DATA
              )
  
      return {
          "shortname": "SPC",
          "name": "Select Percentile Classification",
          "handles_regression": False,
          "handles_classification": True,
          "handles_multiclass": True,
          "handles_multilabel": False,
          "handles_multioutput": False,
          "is_deterministic": True,
          "input": (SPARSE, DENSE, data_type),
          "output": (INPUT,),
      }
  
file_path: auto-sklearn/autosklearn/pipeline/components/feature_preprocessing/select_percentile_classification.py
imports: from typing import Optional
  from functools import partial
  from ConfigSpace.configuration_space import ConfigurationSpace
  from ConfigSpace.hyperparameters import CategoricalHyperparameter, Constant, UniformFloatHyperparameter
  from autosklearn.askl_typing import FEAT_TYPE_TYPE
  from autosklearn.pipeline.components.base import AutoSklearnPreprocessingAlgorithm
  from autosklearn.pipeline.components.feature_preprocessing.select_percentile import SelectPercentileBase
  from autosklearn.pipeline.constants import DENSE, INPUT, SIGNED_DATA, SPARSE, UNSIGNED_DATA
label_desc: Use image node_id 4 for calling the SelectPercentileClassification obj's underlying member method code with example usage: obj.get_properties(dataset_properties) and returns: dict