Answers.Body: <p>You’re looking for an algorithm with identifies the explained variance of each feature.  The first to my mind was Principal Component Analysis.  But the more I thought about it, I personally am more comfortable with decision trees and their interpretability will often give a similar insight.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-04-02T13:41:14.220Z
Answers.LastActivityDate: 2024-04-02T13:41:14.220Z
Answers.UserDisplayName: foreverska
Body: <p>I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/factors that contribute the highest towards the academic performance of the students. Which machine learning algorithm is the most suitable for this task?</p>
  <p>A friend suggested using clustering algorithm that can segment the students into different performance groups, but I think that will not solve my problem.</p>
  
Tags: <machine-learning><prediction><algorithm-request><features>
Title: Machine Learning Algorithm for identifying the factors contributing to academic performance of students
UserDisplayName: Dawood Ahmad
ThreadText: # Machine Learning Algorithm for identifying the factors contributing to academic performance of students
  
  (Asked by: username_0 on 2024-04-02)
  
  I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/factors that contribute the highest towards the academic performance of the students. Which machine learning algorithm is the most suitable for this task?
  
  A friend suggested using clustering algorithm that can segment the students into different performance groups, but I think that will not solve my problem.
  
  **Tags:** machine-learning, prediction, algorithm-request, features
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2024-04-02. Score: 1
  
  You’re looking for an algorithm with identifies the explained variance of each feature. The first to my mind was Principal Component Analysis. But the more I thought about it, I personally am more comfortable with decision trees and their interpretability will often give a similar insight.
  
  
  ---
  
  