INFS4203/7203 Project Phase II (20 marks)
Semester 2, 2021
Due date:
16:00 on 29th October 2021(Brisbane Time) (Phase II, 20%)
All assignments should be submitted to UQ Blackboard only. If any assignment is failed to be submitted
appropriately before due, a penalty will be applied according to ECP. It is your responsibility to ensure
your submission is successful before due time. Email submission will not be accepted.
Overview
In Phase II, you will implement your proposal submitted in Phase I, with necessary adjustment according
to the empirical performance and the feedback from the proposal. This is an individual assignment. The
completion of the assignment should be based on your own design and feedback from the proposal.
Track 1: Data-oriented project
In Phase II, you will be provided with the test data named Ecoli_test.csv. The first row describes features’
names. Except the first row, each row in the data file corresponds to one data point. There are 917 test
data points in this file, and each column represents the same feature as the training data Ecoli.csv. Note
that the test data only has 116 columns, without labels, i.e., the final column “Target (Column 117)” in
Ecoli.csv.
In this phase, you will need to implement the ideas in your proposal and use them to classify the test data.
You need to submit
A result report on
o Test result: the prediction on test data and
o Evaluation result: the evaluated accuracy and F1 on the training data using cross-
validation.
A readme file with clear and thorough description of your coding environment (operation system,
programming language and its version, additional packages installed etc.) and instructions on how
to run the code such that your reported test and evaluation results can be reproduced.
Your implemented code which has a main function to generate the test and evaluation results of
classification.
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Format
The result report should be named as sxxxxxxx.csv (sxxxxxxx is your student username). For
example, if your student username is s1234567, then the result report should be named as
s1234567.csv.
The result report should be composed of 918 rows. For the first 917 rows, the th row gives the
prediction of the th test instance, either 1 or 0. The last row (row 918) gives the accuracy (first
column, rounded to the nearest 3rd decimal place) and F1 (second column, rounded to the
nearest 3rd decimal place) evaluated by yourself through cross-validation on the training data.
You could refer to result_report_example.csv, which provides an example (NOT groundtruth) of
the result report.
Note that result report submitted in other forms or names will not be accepted or marked.
Together with the result report, you need to submit a readme file and all your code.
The readme file and your code should be compressed into one zip file named sxxxxxxx.zip
(sxxxxxxx is your student username).
Note that code and readme file submitted in other forms or names will not be accepted or marked.
We recommend you follow the Google Style Guides (https://google.github.io/styleguide/) for the
programming style, which is not mandatory for this assignment, but using it may benefit your future
career as a data scientist.
Submission
Only your submitted version will be marked. All required files need to be submitted before due. Otherwise,
penalty will be applied according to ECP, i.e.,
10% of the maximum possible mark for the assessment item will be deducted per calendar day (or part
thereof), up to a maximum of seven (7) days. After seven days, no marks will be awarded for the item. A
day is considered to be a 24-hour block from the assessment item due time. Negative marks will not be
awarded.
Result report should be submitted through the “Report submission” Turnitin link provided on
Blackboard -> Assessment -> Project Phase II -> Report submission before the deadline.
Compressed file of readme and code should be submitted through the “Readme and code
submission” Turnitin link provided on Blackboard -> Assessment -> Project Phase II -> Readme
and code submission before the deadline.
Marking standard
Submissions satisfying both the following two will be accepted and marked
1. The test and evaluation results can be reproduced by the submitted readme file and code.
2. The test and evaluation results are generated by applying classification techniques to the data.
When the above two conditions are satisfied, the result report will be marked according to the F1 result
on the test data in the following way (rounded to the nearest 1st decimal place)
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For F1 less than or equal to 0.2: Mark = F1 / 0.2 * 8
For F1 greater than 0.2 but less than 0.7: Mark = (F1-0.2) / 0.5 * 5 + 8
For F1 greater than or equal to 0.7 but less than 0.9: Mark = (F1-0.7) / 0.2 * 7 + 13
For F1 greater than or equal to 0.9: Mark = 20
Please see the example below
F1 Mark
0.1 4
0.2 8
0.3 9
0.4 10
0.5 11
0.6 12
0.7 13
0.8 16.5
0.9 20
Pre-submission feedback (optional)
If you want to get evaluation feedbacks before the due time, you could submit a pre-submission report
file (with the same format and file name as the result report file) before Oct 19th 16:00 pm through
Blackboard -> Assessment -> Project Phase II -> Pre-submission feedback (optional).
Oct 19th 16:00 pm is a firm deadline. Late submission will not be assessed and provided with feedback.
File submitted in other forms or names will not be accepted.
Feedback will be provided based on the submitted pre-submission report file.
Track 2: Competition-oriented project
In this phase, you need to submit:
A result report of the Public Leader Board results, including a screenshot and an URL of the Public
Leader Board.
A readme file with clear and thorough description of your coding environment (operation system,
hardware requirement, programming language and its version, additional packages installed etc.)
and instructions on how to run the code such that your final submission to Kaggle can be
reproduced
Your implemented code which has a main function to generate the final submission to Kaggle.
Your submission will be marked according to the marking standard specified in “Project Specification”
released in Week 2.
Format
The result report should be named as sxxxxxxx.pdf or sxxxxxxx.doc/docx (sxxxxxxx is your student
username). For example, if your student username is s1234567, then the result report should be
named as s1234567.pdf/doc/docx.
Note that result report submitted in other forms or names will not be accepted or marked.
Together with the report, you need to submit all your code and a readme file. The readme file and
your code should be compressed into one zip file named sxxxxxxx.zip (sxxxxxxx is your student
username).
Note that code and readme file submitted in other forms or names will not be accepted or marked.
Submission
Only your submitted version will be marked. All required files need to be submitted before due. Otherwise,
penalty will be applied according to ECP.
Result report should be submitted through the “Report submission” Turnitin link provided at
Blackboard -> Assessment -> Project Phase II -> Report submission before the deadline.
Compressed readme file and code should be submitted through the “Readme and code
submission” Turnitin link provided at Blackboard -> Assessment -> Project Phase II -> Readme
and code submission before the deadline. Note that the zip file should be smaller than 100MB. If
your file is larger than 100MB,before
due time by email in case there is any penalty applied to later submission.