Association Rule

Prepare rules for the all the data sets

• Try different values of support and confidence. Observe the change in number of rules for different support,confidence values
• Change the minimum length in apriori algorithm
• Visulize the obtained rules using different plots

Books Data

• EDA
• Apriori Algorithm

with, min_support =0.1

• Getting Rules

with, metric="lift", min_threshold=0.7

• Visualizing

• Changing Parameters

with, metric="lift", min_threshold=2

• Checking Confidence > 0.5

Therefore, for support>0, confidence>0.5, lift>2 we get 25 rules, with ItalCook and CookBks as most optimum rule

Movies Data

• EDA
• Apriori Algorithm

with, min_support =0.1

• Getting Rules

with, metric="lift", min_threshold=0.7

• Visualizing

• Changing Parameters

with, metric="lift", min_threshold=5

• Checking Confidence > 0.5

Therefore, we get the most optimum results for support>0.1, confidence>0.5, and lift>5