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from sklearn.datasets import load_iris from sklearn import tree X, y = load_iris(return_X_y=True) clf = tree.DecisionTreeClassifier() clf =…
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from sklearn import tree clf = tree.DecisionTreeClassifier() # [height, weight, shoe_size] X = [[181, 80, 44], [177, 70, 43], [160, 60, 38], [154,…
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import pandas as pd from sklearn.tree import DecisionTreeClassifier data = pd.DataFrame() data['A'] = ['a','a','b','a'] data['B'] = ['b','b','a','b']…
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if A>0.4 then if B0.8 then class='X' In order to extract the decision rules, we can use the following code. from sklearn.tree import _tree def…
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Reading all the lines at a time is possible but can be ricky so to process the line one at a time for reading, we can do the following processFile =…
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To iterate over a list, we have to define a list li
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Let us assign all the recorded time in a variable x=c(17,16,20,24,22,15,21,15,17,22) To find out the time he commuted 20 minutes or more, we can do…
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Let us assume the following vector count_list
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In R, names() function is used to assign names to each element in a vector. Let us assign a vector named temps which contains temperature of seven…
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We will read the dataset which is a bank data bank
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A data frame is a structure having 2 dimensions which contains data in the form or rows and columns.It is like a spreadsheet or dictionaries of…
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The approach we can usually use is to manipulate the factor values so we can plug them into the hcl() function. First, some raw data:…
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