Reference no: EM132975873
DATA4800 Artificial Intelligence and Machine Learning - Kaplan Business School
Assessment - Group Case Study and Individual Exercise
Your Task
Group Component: Analyse the dataset pertaining to diabetes in a segment of the population that will be provided. Discuss the findings and present insights to the class.
Individual Component: Individually summarise the learnings and suggest additional techniques in a brief report.
Background: We have explored a number of Machine Learning techniques in class. We also observed that that it is possible to abstract these methods using a tool such as Spotfire that has menu driven implementations.
In this assessment you will create a machine learning model that can describe the data and report of the characteristics of the model and its potential for predicting future cases.
Part A
As a group:
• Load the dataset into Spotfire or your preferred machine learning method
• Create plots that would enable you to assess the characteristics of data
• Create notes for the presentation). As individuals,
1. Write dot points on this section in your own words (100 words)
Part B
As a group:
Select and appropriate machine learning method, create a model and run the model:
1. What is an appropriate machine learning method to predict diabetes in a patient?
2. What was your output from running the model (accuracy, ROC curve)?
3. Discuss what other methods you could use for prediction?
4. Create notes for presentation
As individuals,
• Write dot points in your own words on the forecasting techniques (200 words).
Part C
As a group, prepare a presentation (10 minutes):
• Present your answers to questions 1-4 from Part B
• You are encouraged to use the BI tool as a method of presentation
• Include key findings
• Highlight methodology.
• All members of the group should be involved in the presentation
As individuals,
• Write dot points in your own words on ways in which the dataset, visualisations and forecasts could be improved (200 words).
Attachment:- Artificial Intelligence and Machine Learning.rar