Pattern Discovery Using Apriori and Ch-Search Algorithm
The association rule describes and discovers the relations between variables in large databases. Generally, association rules are based on the support and confidence framework. In Apriori algorithm, association rules are used for finding minimum support and minimum confidence. But this method can lead to loss of rules i.e. negative rules are lost. Hence, Ch-search algorithm is introduced which uses its strongest rule i.e. commonly used the coherent rule which promotes information correctness and leads to appropriate decision making among the same item sets.