Created
July 1, 2019 23:09
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tree.py
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from collections import Counter | |
def split(dataset, labels, column): | |
data_subsets = [] | |
label_subsets = [] | |
counts = list(set([data[column] for data in dataset])) | |
counts.sort() | |
for k in counts: | |
new_data_subset = [] | |
new_label_subset = [] | |
for i in range(len(dataset)): | |
if dataset[i][column] == k: | |
new_data_subset.append(dataset[i]) | |
new_label_subset.append(labels[i]) | |
data_subsets.append(new_data_subset) | |
label_subsets.append(new_label_subset) | |
return data_subsets, label_subsets | |
def gini(dataset): | |
impurity = 1 | |
label_counts = Counter(dataset) | |
for label in label_counts: | |
prob_of_label = label_counts[label] / len(dataset) | |
impurity -= prob_of_label ** 2 | |
return impurity | |
def information_gain(starting_labels, split_labels): | |
info_gain = gini(starting_labels) | |
for subset in split_labels: | |
info_gain -= gini(subset) * len(subset)/len(starting_labels) | |
return info_gain | |
class Leaf: | |
def __init__(self, labels): | |
self.predictions = Counter(labels) | |
class Internal_Node: | |
def __init__(self, | |
feature, | |
branches): | |
self.feature = feature | |
self.branches = branches | |
def print_tree(node, spacing=""): | |
"""World's most elegant tree printing function.""" | |
question_dict = {0: "Buying Price", 1:"Price of maintenance", 2:"Number of doors", 3:"Person Capacity", 4:"Size of luggage boot", 5:"Estimated Saftey"} | |
# Base case: we've reached a leaf | |
if isinstance(node, Counter): | |
print (spacing + str(node)) | |
return | |
# Print the question at this node | |
print (spacing + "Splitting") | |
# Call this function recursively on the true branch | |
for i in range(len(node)): | |
print (spacing + '--> Branch ' + str(i)+':') | |
print_tree(node[i], spacing + " ") |
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