bravotty / DataMining_DecisionTree

An Implementation of CART DecisionTree

DataMining_DecisionTree

A python implementation of Decision Tree
Env : Python2.6

Usage :

Windows :

1. Anaconda command  : activate "python2.x env"
2.                     pip/conda install numpy, pydotplus, pandas
3. Download GraphViz : https://graphviz.gitlab.io/_pages/Download/Download_windows.html
4.                     add the GraphViz to your PATH env

Mac & Linux :

1.pip install numpy, pydotplus, pandas
Linux 2.sudo apt-get install graphviz
Mac   2.brew install graphviz

Run .py

python DecisionTree.py

Defination :

DecisionTree Node

class DecisionTree(object):
    def __init__(self, value=None, trueBranch=None, falseBranch=None, results=None, col=-1, summary=None):
        self.value = value               #Record the value in TreeNode
        self.trueBranch = trueBranch     #True  branch in TreeNode
        self.falseBranch = falseBranch   #False branch in TreeNode
        self.results = results           #feature num - Dictionary  
        self.col = col                   #Record the feature columns
        self.summary = summary           #Every Node's summary info for graph

Code Flie :

tools.py 
  |--Evaluation Function
  |--/* MaxMin scalar Function */ hidden 
  |--Accuracy Function
  |--Classify Function
  |--CreateDataSet Function

DecisionTree.py
  |--buildDecisionTree Function
  |--DecisionTreeModelMain Function
  |--Main Function

DecisionPlot.py
  |--createDataSet Function
  |--plot Function
  |--dotgraph Function

fruit.png - Random Decision Tree Generation Figure

DecisionTreeResultPng (File)- 10 random results of Decision Tree Figure
  Show code with opencv :
  |--     import cv2
  |--     fruitPng = cv2.imread("./DecisionTreeResultPng/fruit" +str(3)+".png")
  |--     cv2.imshow('fruitPng.jpg', fruitPng)
  |--     cv2.waitKey(5000)

License

The MIT License