class_docstr: Simple class that holds information on what a problem type is capable of doing.
  
  Parameters
  ----------
  can_predict : bool
      Whether models for this problem type have the ability to predict via `model.predict(...)`.
  can_predict_proba : bool
      Whether models for this problem type have the ability to predict probabilities via `model.predict_proba(...)`.
  is_classification : bool
      Whether this is considered a classification problem type.
      For example:
          `binary`, `multiclass`, and `softclass` are considered classification problem types.
          `regression` and `quantile` are not considered classification problem types.
code: def __init__(
      self,
      can_predict: bool,
      can_predict_proba: bool,
      is_classification: bool,
  ):
      self.can_predict = can_predict
      self.can_predict_proba = can_predict_proba
      self.is_classification = is_classification
  
file_path: autogluon/core/src/autogluon/core/problem_type.py
imports: from typing import Dict, List
  from .constants import BINARY, MULTICLASS, QUANTILE, REGRESSION, SOFTCLASS
label_desc: Use image node_id 1 to create a new ProblemType object  with example: obj = ProblemType(can_predict, can_predict_proba, is_classification)