code: def __init__(self):
      # Determines if sample shall be classified as -1 or 1 given threshold
      self.polarity = 1
      # The index of the feature used to make classification
      self.feature_index = None
      # The threshold value that the feature should be measured against
      self.threshold = None
      # Value indicative of the classifier's accuracy
      self.alpha = None
  
file_path: ML-From-Scratch/mlfromscratch/supervised_learning/adaboost.py
imports: from __future__ import division, print_function
  import numpy
  import math
  from sklearn import datasets
  import matplotlib.pyplot
  import pandas
  from mlfromscratch.utils import train_test_split, accuracy_score, Plot
label_desc: Use image node_id 1 to create a new DecisionStump object  with example: obj = DecisionStump()