It represents the apriori algorithm technique which is quite normal in the data mining. It uses when the clusters are formed. The cluster is also an representation of unsupervised data.

1. apriori algorithm :
Presented by :
K .M .V. Krishna sai
22761A1295

2. Apriori algorithm statement :
Apriori algorithm is the first association rule mining algorithm that
pioneering the use of support based pruning (removing/deleting) to
systematically control the exponential growth of candidate item sets.
Apriori algorithm proceeds by identifying the frequent individual items in database and
extending them to larger and larger item sets as long as those item sets appear
sufficiently in the database.

3. The flowchart of Apriori algorithm can be drawn as :
Item sets
Generate k-item set
candidate (Join step)
Check support
(pruning)
Frequent
Item sets
Set of k -1
frequent item
sets is PI
STOP

4. Example of Apriori algorithm :
Releases of films by music directors in a month :

5. Item set :
MONTH MUSIC DIRECTORS
JANUARY KEERAVANI,THAMAN
FEBRUARY KEERAVANI , THAMAN ,DSP ,
MANI SHARMA
MARCH THAMAN , ANIRUDH , DSP ,
A.R. RAHAMAN
APRIL THAMAN , KEERAVANI ,
ANIRUDH , DSP
MAY KEERAVANI , THAMAN ,
ANIRUDH , A.R.RAHAMAN

6. CANDIDATE SET 1 :
MUSIC DIR SUP COUNT
DSP 3
KEERAVANI 4
A.R.RAHAMAN 2
ANIRUDH 4
THAMAN 4
MANISHARMA 1
CANDIDATE SET 2:
MUSIC DIR SUP COUNT
DSP,KEERAVANI 2
DSP , ANIRUDH 3
DSP , THAMAN 2
KEERAVANI ,
ANIRUDH
3
KEERAVANI ,
THAMAN
3
ANIRUDH ,
THAMAN
3
AS THEY ARE
BELOW THAN
THE MINIMUM
SUPPORT COUNT
THEY ARE
REMOVED

7. CANDIDATE SET 3:
MUSIC DIR SUP COUNT
KEERAVANI , ANIRUDH , THAMAN 2
It is the frequent item set .
The support count is less than 3 and it becomes the solo candidate item set .

8. THANK YOU …….