PROJECT 2: PREDICTIVE MODEL DEVELOPMENT
You are to develop a classification on data set from your Project 1 using Neural Network Technique and three classification techniques (Decision tree, Neural Network Classification, Naive Bayes, and SVM (use Weka/Rapid Miner/Python)
Title of Report: COMPARATIVE STUDY ON XXX CLASSIFICATION
Basic Requirement.
Your paper format should follow report guide (Springer Writing Format) and Your paper should NOT exceed 15 pages. The rest of details need to be in the APPENDIX
Organization of your paper/report.
Your paper should contain the following sections:
1. Introduction (1/2 page)
Description on your dataset and business goal
2. Related Work (1-2 pages)
This section should highlight the related work and any previous work that use the methods (NN.l Decision Tree, Naive Bayes and SVM) on similar data as yours. Some references are required here You MUST provide at least FIVE related work in EACH technique and preferable if the paper used the same data as you use as one of their experimental dataset.
3. Classification Methods (1-2 pages)
A review on the classifications methods used. Just brief.
4. Modelling and Measurement Methods. (1-2 pages)
Describe the modelling set-up (k-cross validation/leave one out/etc) and measurement metrics(accuracv. precision. recall. confusion matrix AUc. RoO used in vou proiect.l
5. Results and Discussion (3-6 pages)
This section should contain the experimental results and analysis of the results. How you compare the classification methods? What measure you use for all three methods. You should present your detail result as appendixes and summarise results in main documents with several tables and graphs.
Example of result table (PLEASE REFER APPENDIX TABLE OF RESULT)
5.1 Visualise Your Results
How you analyse? How you reach to the best technique? Discuss the conclusion of the result describing the issue of Accuracy, Robustness, Interestingness, Error analysis-are there any patterns in the errors made by the models produced, Speed, Scalability and Interpretability.
5.2 Knowledge Analysis
This Section contain the analysis of knowledge.
6. Conclusion and Suggestion (1 page)
This section should contain conclusion of your work, limitation of the techniques, data or tool or any other problems.
Suggestion for future improvements
References
You should refer to several (at least 5 data analytics research paper similar to your work, see how the researchers analyze their problems and results and see how they write research paper.
HAPPY WORKING