What is the difference between Apriori and Eclat algorithms? What is the difference between Apriori and Eclat algorithms in association rule mining?
 A: Here is a good description:
http://www.slideshare.net/wanaezwani/apriori-and-eclat-algorithm-in-association-rule-mining
In particular, apriori is probably the first association rule mining and computationally complex. This leads to the introduction of further fast algorithms. 
A: *

*Apriori is useable with large datasets and Eclat is better suited to small and medium datasets.

*Apriori scans the original (real) dataset, whereas Eclat scan the currently generated dataset.

*Apriori is slower than Eclat.
A: *

*Apriori algorithm is a classical algorithm used to mining the frequent item sets in a given dataset.

*Coming to  Eclat algorithm also mining the frequent itemsets but in vertical manner and it follows the depth first search of a graph.

*As per the speed,Eclat is fast than the Apriori algorithm.

*Apriori works on larger datasets where as Eclat algorithm works on smaller datasets. 
A: Look this article:
Comparing Dataset Characteristics that Favor the
Apriori, Eclat or FP-Growth Frequent Itemset
Mining Algorithms

Apriori is an easily understandable frequent itemset mining
algorithm. Because of this, Apriori is a popular starting
point for frequent itemset study. However, Apriori has serious
scalability issues and exhausts available memory much faster
than Eclat and FP-Growth. Because of this Apriori should not
be used for large datasets.

