程序代写代做代考 graph data mining RMIT University

RMIT University
School of Science COSC2110/COSC2111 Data Mining
Guidelines for report on “Part 3: Data Mining”
Who is the reader? As in all reports, it is important to keep the reader in mind. In this
case:
1
1. Lecturer/Tutor
2. An independent reader unfamiliar with the project who needs to determine whether a fair mark has been given for the work done.
Introduction
Describe the data, where it comes from and the kinds of results and insights you would like to get.
2 Body
A series of subsections with the following structure:
2.1 Question/Hypothesis
What question are you asking and why.
2.2 Data Preparation, Preprocessing
I think it¡¯s good to include a brief extract from the data file(s).
2.3 Data Mining Technique
The data mining technique to be used and how any relevant parameters were chosen and explored.
2.4 Results
The results of applying the technique to the data. Could be graphs or tables or images.
2.5 Conclusions
Conclusions/insights golden nuggets about the question/hypothesis
3 Overall Conclusions
Stand back from the detail and give give the significant findings, golden nuggets and conclusions about the whole project.
Data Mining 1 12-Sep-2020