This is the home page of the competition. As the tagline of the competition suggests your task is to classify the datapoints using clustering techniques. You have been provided with a dataset with 24 attributes and 1031 instances and your task is to classify the given dataset into 3 classes [0,1,2] using only
Clustering
algorithms.
A Brief Overview of Dataset
The given dataset contains the following 24 attributes:
id:
Unique identity number
Account1:
Accounts of type-1
Monthly Period:
Duration in month
History:
Types of client histories
Motvie:
Types of client motives
Credit1:
Credit amount
Account2:
Accounts of type-2
Employment Period:
Time Period of workers' employments
InstallmentRate:
self-explanatory
Gender&Type:
self-explanatory
Sponsors:
Types of sponsors
Tenancy Period:
Residence period
Plotsize:
self-explanatory
Age:
self-explanatory
Plan:
Type of plan action
Housing:
Type of residence owned
#Credits:
Rate of credits
Post:
His/Her job post
#Authorities:
Total number of authorities engaged
Phone:
If phone is available or not
Expatriate:
Is he/she working for a foreign agency
InstallmentCredit:
Credit received for installment
Yearly Period:
Duration in years
Class:
Target variable
Note:
These kinds of datasets are normally collected through online or offline forms. Hence the dataset may be imperfect in many ways. Thus identifying and correcting all of those imperfections will most likely give you better results. All the best!! =D