class_docstr: Boosting method that uses a number of weak classifiers in 
  ensemble to make a strong classifier. This implementation uses decision
  stumps, which is a one level Decision Tree. 
  
  Parameters:
  -----------
  n_clf: int
      The number of weak classifiers that will be used. 
code: def __init__(self, n_clf=5):
      self.n_clf = n_clf
  
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 Adaboost object  with example: obj = Adaboost(n_clf)