This document summarizes the results of using k-means clustering on four datasets prior to classification with decision trees. For each dataset, k-means clustering was performed with 2, 4, and 6 clusters, and a decision tree classifier was applied to the clustered data. Accuracy improved in most cases after clustering compared to directly applying the decision tree without clustering. Clustering helped increase classification accuracy by grouping similar instances together for three of the four datasets.

1. United International University
​​Assignment-01
​​Title: Classification by Clustering.
Course : Pattern Recognition Lab
Course Code : CSI 416
Submitted To :
Dr.Dewan Md.Farid
Associate Professor,CSE
United International University.
Submitted By :
Nazmul Hyder
Id : 011 131 085
Section : SB
Date : 06.08.2017

2. Dataset 1: Mushroom
Data set
characteristics:
Multivariat
e
Number of
instances :
8124 Area : Life
Attribute
characteristics:
Categorical Number of
attribute :
22 Data
denoted:
1987-09-01
Associate Task: Classificat
ion
Missing values: Yes Number of
web hits :
261721
Using Decision Tree (j4.8) :
Accuracy : 66.9621%
Error : 33.0379%
After simple k means clustering :
Number of cluster:2
Using DT(j4.8):
Accuracy : 99.4953%
Error : 0.5047%
Number of cluster:4
Using DT(j4.8):
Accuracy : 99.8523%
Error : 0.1477%
Number of cluster:6
Using DT(j4.8):
Accuracy : 99.483%
Error : 0.517%
Observation : Accuracy increased after the clustering compared to the initial accuracy .
Dataset 2: Wine-Quality-Red
Data set
characteristics:
Multivariat
e
Number of
instances :
1599 Area : Business
Attribute
characteristics:
Real Number of
attribute :
12 Data
denoted:
2009-10-07
Associate Task: Classificat
ion,
Regression
Missing values: No Number of
web hits :
475478
Using Decision Tree (j4.8) :
Accuracy : 90.9944%
Error : 9.0056%

3. After simple k means clustering :
Number of cluster:2
Using DT(j4.8):
Accuracy : 99.1245%
Error : 0.8755%
Number of cluster:4
Using DT(j4.8):
Accuracy : 97.8737%
Error : 2.1263%
Number of cluster:6
Using DT(j4.8):
Accuracy : 97.8737%
Error : 2.1263%
Observation : Accuracy increased after the clustering compared to the initial accuracy .
Dataset 3 : ZOO
Data set
characteristics:
Multivariat
e
Number of
instances :
101 Area : Life
Attribute
characteristics:
Categorical
, Integer
Number of
attribute :
17 Data
denoted:
1990-05-15
Associate Task: Classificat
ion
Missing values: No Number of
web hits :
172527
Using Decision Tree (j4.8) :
Accuracy : 99.0196%
Error : 0.9804%
After simple k means clustering :
Number of cluster : 2
Using DT(j4.8):
Accuracy : 100%
Error : 0%
Number of cluster : 4
Using DT(j4.8):
Accuracy : 97.0588%
Error : 2.9412%
Number of cluster : 6
Using DT(j4.8):
Accuracy : 96.0784%
Error :3.9216%
Observation : Accuracy increased after the clustering compared to the initial accuracy .

4. Dataset 3 : flags
Data set
characteristics:
Multivariate Number of
instances :
194 Area : N/A
Attribute
characteristics:
Categorical,
Integer
Number of
attribute :
30 Data
denoted:
1990-05-15
Associate Task: Classificati
on
Missing values: No Number of
web hits :
159411
Using Decision Tree (j4.8) :
Accuracy : 81.9588%
Error : 18.0412%
After simple k means clustering :
Number of cluster : 2
Using DT(j4.8):
Accuracy : 92.7835%
Error : 7.2165%
Number of cluster : 4
Using DT(j4.8):
Accuracy :88.6598%
Error :11.3402%
Number of cluster : 6
Using DT(j4.8):
Accuracy : 86.5979%
Error :13.4021%
Observation : Accuracy increased after the clustering compared to the initial accuracy .