Apriori algorithm
Apriori algorithm is a group of set rules that guide data mining. The data is used in predicting future outcomes in the business. Apriori algorithm identifies the most frequent itemset and their relevant regulations attached to them. It is preferably used in a database that contains large numbers of transaction records to confirm the procedures followed by both customer and sellers. Apriori algorithm is advantageous in market basket analysis and allows the customer to purchase their required items with ease hence leading to increased sales of the market. It is also used in the medical sector to detect the adverse reaction of a drug on the patient’s body. Apriori algorithm is also used in organizations to learn and explore relations among variables in an extensive database of the firms. It helps in selecting the interesting rules from multiple rules that may arise from a small database through comparison of constraints on various measures of interest and significance.
Apriori algorithm is perceived as part of a frequent itemset mining since it uses the concept of frequent itemset to generate associated rules in data mining. It guides how many itemsets appear in a database for the establishment of the law that governs its mining. It is used to scan the database repeatedly to calculate the support count of each itemset. Apriori algorithm is modified to the best design that suits the mining of various sets of devices. The associated rule established is easily adapted through the use of the Apriori Algorithm that ensures the users understand which law to apply when mining data from the transaction records. Apriori algorithm is implemented in the education field to extract associated rules of data mining of the students their characteristic and specialization fields. In the medical field, the algorithm is used in analyzing the patient’s database and identify drug combination that he or she is prescribed on usage. It is also applied in forestry to examine the possibilities and impacts caused by fires in conjunction with forestry fire data records. Many companies employ the apriori algorithm in recommender systems to auto-complete the installing features.