Association rule learning is a machine learning method for discovering interesting relationships between variables in large databases. It aims to find rules that describe large portions of your data with high accuracy (support and confidence). Some common algorithms for learning association rules include Apriori, Eclat, and FP-Growth algorithms.

1. ASSOCIATIO
N RULE
ECLAT
Sharing Session

2. Association
Rule
adalah metode pembelajaran
mesin berbasis Rule untuk
menemukan hubungan yang
menarik antara variabel dalam
database besar.

3. Association
Rule
Apriori algorithm
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2
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Eclat algorithm
FP-Growth algorithm

4. Association
Rule
Support
1
2 Confidence
Dalam association rule ada beberapa
terminologi yang di gunakan :
Support adalah indikasi seberapa sering
itemset muncul dalam dataset.
Contoh: {Sugar,Cofee} = 3/5 = 60%
Confidence adalah indikasi seberapa sering
Aturan terbukti benar.
Contoh: {Milk,Sugar} = 5/5 = 100%

5. 1
2
3
4
5
6
Push chairs in
Lights out
Single file, silent line
Proceed toward the woods
Pass the playground on the right
Count off
Eclat Algorithm

6. EVACUATIO
N
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2
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6
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Push chairs in
Lights out
Single file, silent line
Walk toward the high school
Pass the playground on the left
Proceed to new gym
Count off

7. SHELTER IN PLACE
1
Door closed
and locked
2
Windows covered,
closed, and locked
3
Students may only move
around the building
escorted by an adult
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8. LOCK DOWN
1
2
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Lights out
Door locked
Hide under the tables
Chair pulled toward you
No talking
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9. WEATHER EMERGENCY
1
Know the safety
zone
2
Move quickly and
quietly to the
safety zone
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