University | Singapore Management University (SMU) |
Subject | Machine Learning |
The aim would be to compare various models and techniques for their estimation to allow meaningful interpretation and competitive predictive performance. The latter should be assessed by appropriate experiments based on training and test datasets. In addition to linear regression, Tree-based methods, Non-linear models, or other suitable techniques can be used if you think they can provide improvement.
Task:
Build a regression model for the variable G3 (final grade) without using the variables G1 and G2. Interpret the model and assess its predictive performance.
Stuck with a lot of homework assignments and feeling stressed ? Take professional academic assistance & Get 100% Plagiarism free papers
Get done your Machine Learning coursework from the Singapore Assignment Help. Our writers are highly educated to offer the finest quality coursework writing help on artificial intelligence, computer science, FIN525 Machine Learning, Deep Learning, and Applications in Finance Assignment. Our experts support 24 hours line to resolve your all doubt related to computer science assignments at a pocket-friendly price.
Looking for Plagiarism free Answers for your college/ university Assignments.
- INDIVIDUAL RESEARCH PROJECT: MERGERS AND THEIR IMPACT
- PSS388 End of Course Assessment January Semester 2025 SUSS : Integrated Public Safety And Security Management
- PSY205 Tutor-Marked Assignment 02 SUSS January 2025 : Social Psychology
- Math255 S1 Assignment-2025 SUSS : Mathematics for Computing
- BUS100 Tutor-Marked Assignment January 2025 SUSS : Business Skills And Management
- CSCXXX SUSS : New System Development Using Java : Soft Dev Pte Ltd Project
- Cloud Computing: Fundamentals, Networking, and Advanced Concepts
- COS364 Tutor-Marked Assignment January 2025 Sem SUSS : Interventions for At-Risk Youth
- FMT309 Tutor-Marked Assignment 01 SUSS January 2025 : Building Diagnostics
- HBC203 Tutor-Marked Assignment 01 January 2025 SUSS : Statistics and Data Analysis for the Social and Behavioural Sciences