Dwdm 5 exp

 Aim: Demonstration of clustering rule process on iris.arff using simple k means algorithm.

The experiment illustrates the use of simple k-means clustering weka explorer.

The sample data set use for this experiment is iris data in arff format.

Steps involved in experiment:

Step 1:create iris.arff file

@relation iris

@attribute sepallenght numeric

@attribute sepalwidth numeric

@attribute petallenght numeric

@attribute petalwidth numeric

@attribute class{iris-setosa,iris-veriscolor}

@data

5.1,3.5,1.4,0.2,iris-setosa

4.9,3.0,1.4,0.2,iris-setosa

4.3,3.0,1.1,0.1,iris-setosa

7.0,3.2,4.7,1.4,iris-veriscolor

6.4,3.2,4.5,1.5,iris-veriscolor

6.9,3.1,4.9,1.5,iris-veriscolor

6.3,3.3,6.0,1.9,iris-veriscolor

5.8,2.7,5.1,2.1,,iris-veriscolor

7.1,3.0,5.9,1.8,,iris-veriscolor

Step2: From the weka explorer load the data file iris .arff into weka 

Step 3: in order to perform clustering select the cluster tab and click on the choose button. This steps results in dropdown list of available clustering algorithms. 

Step 4: In this case we select simplekmeans  

Step 5: Now click on the text button to right of the choose button. now a popup window is appeared. In this window select number of clusters.

step 6: now we keep on use training set data and run the algorithm.

Step 7: now we click on the start button to generate the model now the evaluation statistics will appear in the right panel.

Output:

=== Run information ===