class_docstr: Base class for applying filtering operations on tabular data 
docstr: Method for fit filter
  
  :param input_data: data with features, target and ids to process
  :return operation: trained operation (optional output)
docstr_tok: ["Method","for","fit","filter",":","param","input_data",":","data","with","features",",","target","and","ids","to","process",":","return","operation",":","trained","operation","(","optional","output",")"]
code: def fit(self, input_data: InputData):
      """Method for fit filter
  
      :param input_data: data with features, target and ids to process
      :return operation: trained operation (optional output)
      """
  
      self.operation.fit(input_data.features, input_data.target)
  
      return self.operation
  
imports: from copy import copy
  from typing import Optional
  import numpy
  import sklearn
  from golem.core.log import default_log
  from pkg_resources import parse_version
  from sklearn.ensemble import IsolationForest
  from sklearn.linear_model import LinearRegression, RANSACRegressor
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import StandardScaler
  from sklearn.tree import DecisionTreeRegressor
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import DataOperationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
label_desc: Use image node_id 2 for calling the FilterImplementation obj's underlying member method code with example usage: obj.fit(input_data) and returns: self