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webin_decision_tree

v0.0.6

Published

Nodejs implementation of decision tree using Entropy algorithm

Downloads

7

Readme

Decision Tree for NodeJS by Kraivit Mongkhonsakunrit Build Status

This module contains the NodeJS Implementation of Decision Tree using Entropy Algorithm

Table Of Contents

Installation

npm install webin_decision_tree

Usage

  • Import the module:(id:importmodule)

      const decision_tree = require('webin_decision_tree');
  • Prepare training dataset:

      "data": [
      {"กล้าหาญ":true, "อดทน":true, "รักอิสระ":true, "classification":{"description":"กล้าหาญ อดทน รักอิสระ"}},
      {"กล้าหาญ":false, "อดทน":true, "รักอิสระ":true, "classification":{"description":"อดทน รักอิสระ"}},
      {"กล้าหาญ":true, "อดทน":false, "รักอิสระ":true, "classification":{"description":"กล้าหาญ รักอิสระ"}},
      {"กล้าหาญ":false, "อดทน":false, "รักอิสระ":true, "classification":{"description":"รักอิสระ"}},
      {"กล้าหาญ":true, "อดทน":true, "รักอิสระ":false, "classification":{"description":"กล้าหาญ อดทน"}},
      {"กล้าหาญ":false, "อดทน":true, "รักอิสระ":false, "classification":{"description":"อดทน"}},
      {"กล้าหาญ":true, "อดทน":false, "รักอิสระ":false, "classification":{"description":"กล้าหาญ"}},
      {"กล้าหาญ":false, "อดทน":false, "รักอิสระ":false, "classification":{"description":"none"}}
      ]
  • Prepare data set Demo:

      "data": [
      {"กล้าหาญ":"กล้าหาญ", "อดทน":"อดทน", "liked":false,"love":true},
      {"กล้าหาญ":"กระจอก", "อดทน":"ขี้กาก", "liked":false,"love":false},
      {"กล้าหาญ":"กล้า", "อดทน":"มีระเบียบ", "liked":true,"love":true},
      {"กล้าหาญ":"สู้", "อดทน":"ไม่กลัว", "liked":true,"love":false},
      {"กล้าหาญ":"ไม่ท้อ", "อดทน":"มีวินัย", "liked":false,"love":true},
      {"กล้าหาญ":"เข็มแข็ง", "อดทน":"ยอมแพ้", "liked":false,"love":true},
      {"กล้าหาญ":"ไม่กลัว", "อดทน":"ไม่สู้", "liked":true,"love":false},
      {"กล้าหาญ":"รับผิดชอบ", "อดทน":"กระจอก", "liked":true,"love":false}
      ]
  • Check Purge:

      const text = "กลัว ทำไมละนั้น ส้ส ควย"
      decision_tree.wordcut(text) //ตัดคำไม่สุขภาพออก

รออัพเดท Path ตอนนี้ยังเป็น Demo อยู่ในระหว่างการพัฒนาระบบ รองรับการทำ Dynamic Function , Muti Class , Muti Sub Node Decision Tree