8. Using 75% minimum confidence and 20% minimum support, generate two-antecedent

Question

8. Using 75% minimum confidence and 20% minimum support, generate two-antecedent association rules for predicting play. For the following several exercises, consider the following data set from Quinlan [4 as Table 12.8. The goal is to develop association rules using the a priori algorithm ing to predict when a certain (evidently indoor) game may be played. Therefore, unlike the vegetable stand example, we may restrict our itemset search to items that include shown the attribute play 4. Let ? 3. Generate the frequent 1-itemsets. 5. Let ?-3. Generate the frequent 2-itemsets. 7, Using 75% minimum confidence and 20% minimum support, generte one-antecedent association rules for predicting play. TABLE 12.8 Weather data set for association rule mining Outlook Temperature Humidity Windy Play False True False False False True True False False False True True False True High High High High Sunny Sunny Overcast Rain Rain Rain Overcast Sunny Sunny Rain Sunny Overcast Overcast Rain Hot Hot Hot Mild Cool Cool Cool Mild Cool Mild Mild Mild Hot Mild No Yes Yes Yes No Yes Normal Normal Normal High Normal Normal Normal Yes Yes Yes Yes Yes 10 12 High Normal High

Explanation / Answer

Based on above conditon, we get the following rule:

1. if Outlook=Overcast, Temperature=Hot & Windy=false then play=yes;

2. if Outlook=Rain, Temperature=Mild & Windy=false then play=yes;

3. if Outlook=Rain, Humidity=Normal & Windy=false then play=yes;

4.Temperature=Cold, Humidity=Normal & Windy=false then play=yes;

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