Dodanie 'id3.py'

id3.py

@@ -0,0 +1,169 @@
+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)
+
+
+    
+
+    
+