• R.SMEETA MARY
• Dr.K.PERUMAL

There are several mining algorithms of association rules. One of the algorithms is very fast maximal frequent itemset that is used to extract frequent itemsets from large database and getting the association rule for discovering the knowledge. Based on this algorithm, this paper indicates the limitation of the very fast maximal frequent itemset of wasting time by substituting the numbers for the whole database searching on the frequent itemsets, and presents an improvement on concept adaptive maximal frequent itemset by reducing the wasted time by substituting the prime values. The paper shows by experimental results with several groups of transactions, and with several values that applied on the very fast maximal frequent itemset and our implemented concept adaptive maximal frequent itemset that our improved algorithm reduces the time consumed in comparison with the very fast maximal frequent itemset, and makes the algorithm more efficient and less time consuming. For implementation of the work patient database is taken and the patient records are experimented and the final best is identified with quick response time and least error rate. A typical confusion matrix is furthermore displayed for quick check. The concept adaptive maximal frequent itemset algorithmic discussion of the heart disease dataset from kaggle, cardiovascularheart2019dataset, repository of large datasets. The Best results are achieved by using R tool. R is an effective data handling and storage facility especially for data mining. By adding the true positive and true negative values, then dividing the total number of possibilities the accuracy is calculated for concept adaptive maximal frequent itemsets.

VFMFI, CMFIA, Frequent Itemsets, Time Consuming.

"CONCEPT ADAPTIVE MAXIMAL FREQUENT ITEMSET ALGORITHM FOR ASSOCIATION RULES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.695-713, May-2019, Available :http://www.jetir.org/papers/JETIR1905W51.pdf

"CONCEPT ADAPTIVE MAXIMAL FREQUENT ITEMSET ALGORITHM FOR ASSOCIATION RULES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp695-713, May-2019, Available at : http://www.jetir.org/papers/JETIR1905W51.pdf