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Updated 3 years ago
Exploring Decision Tree Algorithm
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline
#for encoding
from sklearn.preprocessing import LabelEncoder
#for train test splitting
from sklearn.model_selection import train_test_split
#for decision tree object
from sklearn.tree import DecisionTreeClassifier
#for checking testing results
from sklearn.metrics import classification_report, confusion_matrix
#for visualizing tree
from sklearn.tree import plot_treeC:\Users\Aman Gupta\Anaconda3\lib\site-packages\statsmodels\tools\_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.
import pandas.util.testing as tm
s = pd.Series([30,40,25,35,41,29,45,36,38,43,34,36,42,45,35,28,30,38,43,29,34,42,45,34,40,38,36,54,42,38,29,43,31,50,36,35,46,41,28,36,48,47,39,40,38,32,29,36,46,51,35,46,42,45,41])a = pd.Series([32,35,25,38,45,30,26,43,29,34,50,31,25,34,50,36,28,35,26,38,45,47,38,41,39,41,27,32,34,45,41,29,32,31,28,38,50,48,35,43,36,45,51,29,49,57,56,48,51,36,28,34,51,56,41])c = pd.Series([0,1,0,0,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,0,0,1,1,0,1,0,1,1,1,0,0,1,0,1,1,0,1,0,0,0,1,1,0,1,0,1,0,0,1,1,0,1,0,1,0])