Dodanie 'id3.py'

This commit is contained in:
Cezary Adamczak 2021-05-23 23:15:50 +02:00
parent b9370cb6f9
commit 4c3da838af

169
id3.py Normal file
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from collections import Counter
import operator
from types import prepare_class
import numpy as np
import copy
class Case:
def __init__(self, values, attributes, Class):
self.values = values
self.attributes = attributes
self.Class = Class
class Node:
def __init__(self, Class, tag=None):
self.Class = Class
self.childs = []
def classes_of_cases (cases):
classes = []
for case in cases:
if case.Class not in classes:
classes.append(case.Class)
return classes
def count_classes (cases):
classes = []
for case in cases:
classes.append(case.Class)
c = Counter(classes)
return max(c.items(), key=operator.itemgetter(1))[0]
def chose_attribute (cases, attributes):
a = ""
max = float("-inf")
for attribute in attributes:
if I(cases) - E(cases, attribute) >= max:
max = I(cases) - E(cases, attribute)
a = attribute
return a
def I (cases):
i = 0
all = len(cases)
classes = classes_of_cases(cases)
for Class in classes:
noc = 0
for case in cases:
if case.Class == Class:
noc += 1
i -= (noc/all)*np.log2(noc/all)
return i
def E(cases, attribute):
e = 0
values = []
index = cases[0].attributes.index(attribute)
print(attribute)
print(cases[0].values)
print(index)
for case in cases:
if case.values[index] not in values:
values.append(case.values[index])
for value in values:
ei = []
for case in cases:
if case.values[index] == value:
ei.append(case)
e += (len(ei)/len(cases))*I(ei)
return e
def treelearn(cases, attributes, default_class):
if cases == []:
t = Node(default_class)
return t
if len(classes_of_cases(cases)) == 1:
t = Node(cases[0].Class)
return t
if attributes == []:
t = Node(count_classes(cases))
return t
A = chose_attribute(cases, attributes)
t = Node(A)
new_default_class = count_classes(cases)
print(attributes, end=" ")
values = []
index = attributes.index(A)
print(index)
for case in cases:
if case.values[index] not in values:
values.append(case.values[index])
print(values, end="")
print(A)
for value in values:
new_cases = []
for case in cases:
if case.values[index] == value:
new_case = copy.deepcopy(case)
new_case.values = case.values[:index] + case.values[index+1:]
new_case.attributes = case.attributes[:index] + case.attributes[index+1:]
new_cases.append(new_case)
new_attributes = attributes[:index] + attributes[index+1 :]
child = treelearn(new_cases, new_attributes, new_default_class)
t.childs.append([child, value])
return t
def pretty_print(root, n):
for _ in range(n):
print("\t", end="")
print(root.Class)
for child in root.childs:
for _ in range(n):
print("\t", end="")
print("== " + str(child[1]))
pretty_print(child[0], n+1)
attr = ["hydration", "fertility", "plant_type", "ticks", "is_healthy", "tractor_there"]
ccases = []
k = Case([2, 0, "wheat", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([3, 0, "wheat", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([4, 0, "wheat", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([1, 1, "wheat", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([3, 0, "wheat", 20, 0, 0], attr, 0)
ccases.append(k)
k = Case([2, 0, "wheat", 20, 0, 0], attr, 0)
ccases.append(k)
k = Case([4, 0, "potato", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([3, 0, "potato", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([2, 0, "potato", 31, 0, 0], attr, 0)
ccases.append(k)
k = Case([2, 0, "potato", 31, 0, 0], attr, 0)
ccases.append(k)
k = Case([2, 1, "potato", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([1, 1, "potato", 31, 0, 0], attr, 0)
ccases.append(k)
k = Case([4, 1, "potato", 31, 0, 0], attr, 1)
ccases.append(k)
k = Case([4, 1, "potato", 19, 0, 0], attr, 0)
ccases.append(k)
k = Case([4, 1, "potato", 31, 1, 0], attr, 0)
ccases.append(k)
k = Case([4, 1, "wheat", 19, 0, 0], attr, 0)
ccases.append(k)
k = Case([4, 1, "potato", 31, 0, 1], attr, 0)
ccases.append(k)
k = Case([4, 1, "wheat", 31, 1, 0], attr, 0)
ccases.append(k)
k = Case([2, 0, "wheat", 31, 0, 1], attr, 0)
ccases.append(k)
tree = treelearn(ccases, attr, 0)
pretty_print(tree, 0)