Student Result Prediction using Data Mining

Introduction

This article gives guidelines for the project with WEKA software. As we all know data mining is very popular for analysis and modeling, so the article is for student result prediction using data mining. You will definitely learn about What is WEKA software about and How to use it for analysis and prediction. It is very easy to predict the result using WEKA. You can learn new technologies with Skyfi Labs. We provide the best courses for improvement.

Looking to build projects on Analytics?:

Analytics Kit will be shipped to you and you can learn and build using tutorials. You can start for free today!

1. Data Analytics using R

Project Description

First, discuss WEKA. WEKA stands for Waikato Environment For Knowledge Analysis. It provides a collection of machine learning and data mining software along with a pre-processing tool. It involves algorithms for clustering, classification, regression also associate rile mining and data visualization. It is developed in JAVA. It is very easy to predict information using WEKA. You can try this software for any experimental project with the basic guidelines mentioned below.

Guidelines for Implementation

1. Download the WEKA software. After successful download, you can see three main interfaces I.e. Explorer, Experimental, and Knowledge Flow.
2. After choosing explorer, it consists of different pages like Pre process, classify, cluster associate, select attributes, and visualize. 
3. WEKA accepts the CSV file along with the ARFF file. So input file must be in those formats only. Most of the datasets are in CSV files so no need to worry. You can import the CSV file contains attributes like date, number, name, rank, branch, and result, etc by selecting an open folder option.
4. After choosing the CSV file, you have to click on the Save button which converts CSV file into ARFF format. Also, it removes attribute which does not affect the classification result.
5. Then go to classify page. It consists of many algorithms for classification. For this project, we are choosing the J48 tree algorithm.
6. After starting the classification, you can see the accuracy achieved. So these steps for training data. 
7. Now we have to choose the test file by selecting the supplied test set. In the test file, the result column is totally blank.
8. After that, you can start the prediction and can save the file by clicking on save option.
9. The file will save with .arff extension. You can open it with notepad and can see that the new attribute called student result is predicted with P and F initials.
10. So these are the steps for WEKA explores interface. You can also do it with the use of java.
11. You have to enter the path of WEKA installed files in the command prompt.
12. Create a java file which consists of many packages for WEKA classifiers.
13. It also consists of training and testing data with its location.
14. Run this java file to get the predicted results of students.

Benefits

Introduction to WEKA

Hands-on with WEKA with practical implementation

So these are the simple steps for the student result prediction using the WEKA interface. You can use many algorithms for the prediction of the result. Use the algorithm with the best accuracy. Skyfi Labs provide the course for python and Django, so learn more and keep improving.

Did you know

Skyfi Labs helps students learn practical skills by building real-world projects.

You can enrol with friends and receive kits at your doorstep

You can learn from experts, build working projects, showcase skills to the world and grab the best jobs.
Get started today!

• Python

• Data Mining
• Machine Learning

Student Result Prediction using Data Mining