2. Use OPTICS algorithm to output the reachability distance and the cluster ordering for

the dataset provided, starting from Instance 1. Use the following parameters for

discovering the cluster ordering: minPts =2 and epsilon =2. Use epsilonprime =1.2 to

generate clusters from the cluster ordering and their reachability distance. Don't forget

to record the core distance of a data point if it has a dense neighborhood. You don't

need to include the core distance in your result but you may need to use them in

generating clusters. (45 pts)

10

2

01

012

0²0

OFF

OF

013

02

0¹4

10

OF

ON

04

off

Dataset visualization

8

07

ON

%

06

OD

04

ON

040

of

017

Below are the first few lines of the calculation. You need to complete the remaining lines and

generate clusters based on the given epsilonprime value:

Instance (X,Y) Reachability Distance

Instance 1:

(1, 1)

Undefined (or infinity)

Instance 2:

(0, 1) 1.0

Instance 3:

(1, 0)

1.0

Instance 16: (5,9)

Undefined/nInstance 13: (9, 2)

Instance 12: (8, 2)

***

Undefined

1