MSC-BDT5002辅导、讲解Python、辅导Data Mining、讲解Python语言程序

MSC-BDT5002 Knowledge Discovery

and Data Mining, Fall 2018

Assignment 3

Deadline: Nov. 14th, 11:59 pm ,2018

Task Description

Unsupervised learning is a branch of machine learning that learns from test

data that has not been labeled, classified or categorized. Instead of

responding to feedback, unsupervised learning identifies commonalities in

the data and reacts based on the presence or absence of such commonalities

in each new piece of data. In this assignment, you need to cluster a certain

amount of image data. We will not tell you an exact number of cluster

you should do, you need to find the most appropriate number of

clusters by yourself.

File Description

In total there are 5,011 images.

Sample_submission.csv: The sample submission format you should

follow.

Notes

1. Your assignment will be graded by the clustering accuracy and

clarification for your feature engineering and model details (in

readme.pdf).

2. TA will check your source code carefully, so your code must be

runnable. Keep your code clean and comment it clearly.

3. You can use any programming language. In principle, python is

preferred.

4. Cheating is not allowed. Your result MUST be reproducible.

5. Plagiarism will lead to zero mark.

6. You can use any clustering methods.

Submission Guidelines

1. Assignment should be submitted to mscbdt5002fall18@gmail.com as

attachment.

2. You need to zip the following three files together:

a . A3_itsc_stuid_readme.pdf. Write your feature engineering in it

b . A3_itsc_stuid_code.zip: The zip file contains all your source codes.

c . A3_itsc_stuid_prediction.csv: The clustering result. Each column

stands for one cluster. For example, if you get 8 clusters, your .csv file

should contains 8 columns. The number in the column indicates the

name of the image without a suffix. For example, if the name of an

image is ‘01234.jpg’, you only need to write ‘01234’ into the result.

3. Attachment should be named in the format of: A3_itsc_stuid.zip. E.g.

A3_lliny_20181314.zip

4. Submissions after the deadline or not following the rules above are NOT

accepted.