161 lines
4.3 KiB
Python
161 lines
4.3 KiB
Python
from collections import Counter
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import operator
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from types import prepare_class
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import numpy as np
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import copy
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class Case:
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def __init__(self, values, attributes, Class):
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self.values = values
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self.attributes = attributes
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self.Class = Class
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class Node:
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def __init__(self, Class, tag=None):
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self.Class = Class
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self.childs = []
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def classes_of_cases (cases):
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classes = []
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for case in cases:
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if case.Class not in classes:
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classes.append(case.Class)
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return classes
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def count_classes (cases):
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classes = []
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for case in cases:
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classes.append(case.Class)
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c = Counter(classes)
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return max(c.items(), key=operator.itemgetter(1))[0]
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def chose_attribute (cases, attributes):
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a = ""
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max = float("-inf")
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for attribute in attributes:
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if I(cases) - E(cases, attribute) >= max:
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max = I(cases) - E(cases, attribute)
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a = attribute
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return a
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def I (cases):
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i = 0
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all = len(cases)
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classes = classes_of_cases(cases)
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for Class in classes:
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noc = 0
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for case in cases:
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if case.Class == Class:
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noc += 1
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i -= (noc/all)*np.log2(noc/all)
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return i
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def E(cases, attribute):
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e = 0
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values = []
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index = cases[0].attributes.index(attribute)
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for case in cases:
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if case.values[index] not in values:
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values.append(case.values[index])
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for value in values:
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ei = []
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for case in cases:
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if case.values[index] == value:
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ei.append(case)
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e += (len(ei)/len(cases))*I(ei)
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return e
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def treelearn(cases, attributes, default_class):
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if cases == []:
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t = Node(default_class)
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return t
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if len(classes_of_cases(cases)) == 1:
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t = Node(cases[0].Class)
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return t
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if attributes == []:
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t = Node(count_classes(cases))
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return t
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A = chose_attribute(cases, attributes)
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t = Node(A)
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new_default_class = count_classes(cases)
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values = []
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index = attributes.index(A)
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for case in cases:
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if case.values[index] not in values:
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values.append(case.values[index])
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for value in values:
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new_cases = []
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for case in cases:
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if case.values[index] == value:
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new_case = copy.deepcopy(case)
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new_case.values = case.values[:index] + case.values[index+1:]
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new_case.attributes = case.attributes[:index] + case.attributes[index+1:]
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new_cases.append(new_case)
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new_attributes = attributes[:index] + attributes[index+1 :]
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child = treelearn(new_cases, new_attributes, new_default_class)
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t.childs.append([child, value])
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return t
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def pretty_print(root, n):
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for _ in range(n):
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print("\t", end="")
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print(root.Class)
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for child in root.childs:
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for _ in range(n):
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print("\t", end="")
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print("== " + str(child[1]))
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pretty_print(child[0], n+1)
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attr = ["hydration", "fertility", "plant_type", "ticks", "is_healthy", "tractor_there"]
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ccases = []
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k = Case([2, 0, "wheat", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([3, 0, "wheat", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([4, 0, "wheat", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([1, 1, "wheat", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([3, 0, "wheat", 20, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([2, 0, "wheat", 20, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([4, 0, "potato", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([3, 0, "potato", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([2, 0, "potato", 31, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([2, 0, "potato", 31, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([2, 1, "potato", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([1, 1, "potato", 31, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([4, 1, "potato", 31, 0, 0], attr, 1)
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ccases.append(k)
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k = Case([4, 1, "potato", 19, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([4, 1, "potato", 31, 1, 0], attr, 0)
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ccases.append(k)
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k = Case([4, 1, "wheat", 19, 0, 0], attr, 0)
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ccases.append(k)
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k = Case([4, 1, "potato", 31, 0, 1], attr, 0)
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ccases.append(k)
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k = Case([4, 1, "wheat", 31, 1, 0], attr, 0)
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ccases.append(k)
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k = Case([2, 0, "wheat", 31, 0, 1], attr, 0)
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ccases.append(k)
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tree = treelearn(ccases, attr, 0)
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pretty_print(tree, 0)
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