NodeJS implementation of decision tree using ID3 algorithm
Decision Tree for NodeJS
========================
This module contains the NodeJS Implementation of Decision Tree using ID3 Algorithm
InstallationUsageImport ModulePrepareInstallation* Import the module:
var DecisionTree = require('decision-tree');
* Prepare training dataset:
var training_data = [
{"color":"blue", "shape":"square", "liked":false},
{"color":"red", "shape":"square", "liked":false},
{"color":"blue", "shape":"circle", "liked":true},
{"color":"red", "shape":"circle", "liked":true},
{"color":"blue", "shape":"hexagon", "liked":false},
{"color":"red", "shape":"hexagon", "liked":false},
{"color":"yellow", "shape":"hexagon", "liked":true},
{"color":"yellow", "shape":"circle", "liked":true}
];
* Prepare test dataset:
var test_data = [
{"color":"blue", "shape":"hexagon", "liked":false},
{"color":"red", "shape":"hexagon", "liked":false},
{"color":"yellow", "shape":"hexagon", "liked":true},
{"color":"yellow", "shape":"circle", "liked":true}
];
* Setup Target Class used for prediction:
var class_name = "liked";
* Setup Features to be used by decision tree:
var features = ["color", "shape"];
* Create decision tree and train model:
var dt = new DecisionTree(training_data, class_name, features);
* Predict class label for an instance:
var predicted_class = dt.predict({
color: "blue",
shape: "hexagon"
});
* Evaluate model on a dataset:
var accuracy = dt.evaluate(test_data);
* Export underlying model for visualization or inspection:
var treeModel = dt.toJSON();