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TheSuranaverse / SDS-Mentorship-Program-Task

As a supervised learning algorithm, Decision Tree is used to build a tree structure model for resolving classification and regression problems. The goal of this task is to implement the classification with Decision Tree and evaluate the classification performance with various evaluation methods.
MIT License
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SDS Mentorship Program Task

Task 1 - Build a decision Tree model

Balance Scale Data Set

Decision Tree Model on balance data from UCI -> Dataset

Project Submission Guidelines:

Don't use Github GUI at all, do all work in CLI mode (except for making Pull Request)

  1. First Fork the Repo.
  2. Then go to issue section of my repo.
  3. Search the Issue with your name.
  4. Ask me in Comments to assign the issue to you.
  5. After that you can clone the repo of yours in your local system git clone https://Your/Repo/Name/
  6. Then make a dev branch using -> git checkout -b dev
  7. Upload the project in folder according to name.
  8. Your project files should contain a .gitignore file (So that you don't have to upload redundant files like '.ipynb_checkpoints',etc).
  9. Update the the readme files of your project folder
  10. then add git add . and commit git commit -m "add project files" all your work
  11. to your origin/dev branch using -> git push -u origin dev
  12. And then finally make A Pull Request (from your dev branch to my main branch) by going to your github forked repo.
  13. Write a suitable title and comment in your Pull Request(PR).
  14. If Everything will be fine It'll get merge.

Dataset Description

  1. Title: Balance Scale Weight & Distance Database

  2. Source Information: (a) Source: Generated to model psychological experiments reported by Siegler, R. S. (1976). Three Aspects of Cognitive Development. Cognitive Psychology, 8, 481-520. (b) Donor: Tim Hume (hume@ics.uci.edu) (c) Date: 22 April 1994

  3. Relevant Information: This data set was generated to model psychological experimental results. Each example is classified as having the balance scale tip to the right, tip to the left, or be balanced. The attributes are the left weight, the left distance, the right weight, and the right distance. The correct way to find the class is the greater of (left-distance left-weight) and (right-distance right-weight). If they are equal, it is balanced.

    Data Set Characteristics: Multivariate Number of Instances: 625 Area: Social
    Attribute Characteristics: Categorical Number of Attributes: 4 Date Donated: 1994-04-22
    Associated Tasks: Classification Missing Values? No Number of Web Hits: 291160

  4. Number of Instances: 625 (49 balanced, 288 left, 288 right)

  5. Number of Attributes: 4 (numeric) + class name = 5

  6. Attribute Information:

    1. Class Name: 3 (L, B, R)
    2. Left-Weight: 5 (1, 2, 3, 4, 5)
    3. Left-Distance: 5 (1, 2, 3, 4, 5)
    4. Right-Weight: 5 (1, 2, 3, 4, 5)
    5. Right-Distance: 5 (1, 2, 3, 4, 5)

  7. Class Distribution:

    1. 46.08 percent are L
    2. 07.84 percent are B
    3. 46.08 percent are R