@__username/decision-tree 中文文档教程

Question

Decision Tree for NodeJS

该模块包含决策树的 NodeJS 实现，使用 ID3 算法

Table Of Contents

• Installation
• Usage
  • Import Module
  • Prepare
  • Installation

Installation

npm install decision-tree

Usage

• 导入模块：

  var DecisionTree = require('decision-tree');
  

• 准备训练数据集：

  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}
  ];
  

• 准备测试数据集：

  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}
  ];
  

• 设置目标用于预测的类：

  var class_name = "liked";
  

• 设置决策树要使用的特征：

  var features = ["color", "shape"];
  

• 创建决策树和训练模型：

  var dt = new DecisionTree(training_data, class_name, features);
  

• 预测实例的类标签：

  var predicted_class = dt.predict({
      color: "blue",
      shape: "hexagon"
  });
  

• 评估数据集上的模型：

  var accuracy = dt.evaluate(test_data);
  

• 导出基础模型以进行可视化或检查：

  var treeModel = dt.toJSON();