What is Eclat?
The Eclat model serves to review all combinations and tells you which ones to focus on.
The Eclat algorithm has only one part unlike Apriori:
- Support
It’s very similar to Bayes. Let’s assume that we are doing a movie recommendation.
Because Eclat doesn’t have “confidence” and “lift”, it makes no sense to look at an item by itself in the Eclat model.
The order of progression of eclat
- Step 1.
Set a minimum support. - Step 2.
Take all the subsets in transactions having higher support than the minimum support. - Step 3.
Sort the subsets by decreasing support.
Example
Code
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from apyori import apriori
rules = apriori(
transactions = transactions,
min_support = 0.003,
min_confidence = 0.2,
min_lift = 3,
min_length = 2,
max_length = 2)
results = list(rules)
def inspect(results):
lhs = [tuple(result[2][0][0])[0] for result in results]
rhs = [tuple(result[2][0][1])[0] for result in results]
supports = [result[1] for result in results]
return list(zip(lhs, rhs, supports))
resultsinDataFrame = pd.DataFrame(inspect(results), columns = [
'Product 1',
'Product 2',
'Support'])
resultsinDataFrame = resultsinDataFrame.nlargest(n = 10, columns = 'Support')
Result
