Data mining Essay Example | Topics and Well Written Essays - 1000 words

Data dig - Essay ExampleThe prophetical model work measures predictive scores based on the companys info (Han et al, 2011). The predictive scores produced by the predictive analytics armed services to increase the customer responses during the strategized marketing campaigns. The predictive score also helps in increasing the conversions and clicks, which in turn, help in decreasing the associated churns. Associations discovery in convergences sold to customers The dynamism of the market has direct to the influence on the way the business interacts with their customers. The contemporary market bears no guarantee for the loyalty of a customer. This situation has led to the use of data mining in allowing for associations discovery on the goods sold to the customers. Association discovery harp of rules that use an antecedent (if) and a consequent ( whence) which represent items associated to the obtained customers data (Vaidya et al, 2006). The if is found in the data while then represent an item, which is in integration with the antecedent. The association rules works through analysing the if/then patterns yielded by the customers. The organization then records the patterns to help in identifying the most Copernican relationships. The criteria used involve home run a either pattern as support or confidence. These criteria atomic number 18 important in studying the behavior of the consumer towards the products of any assumption organization. The association rules can be applicable in product flock, catalog design and store layout (Han et al, 2011). weave mining to discover business intelligence from Web customers Web mining is an important application for data mining helping to study the web patterns. This application is important to organizations, which would like to discover then behavior of the web customers. Web mining works through group information from the websites using the traditional data mining whereby there is integration of data obtained from the interaction of the latent customers around the web. Web mining presents the business community with the ability to apply intelligent marketing strategies because of the association about the customers. It helps the business to establish a close relationship with the website customers because of the satisfactory analysis on the market. clustering to find related customer information Clustering in data mining is an important activity for businesses, which helps the latter to find various customers with similar taste to each other. It works through clustering data objects having same attributes concerning the market trend. Through clustering, the firms are able to select mellow-quality clusters that have low inter-cluster similarity and high intra-cluster similarity. This means that the more similarity between members of a cluster than to a member of another cluster. The make for of selecting the clusters in the market is useful in situations where there are many cases with no grouping. The use of clustering algorithms helps in finding the natural groupings. QUESTION 2 Reliability of data mining algorithms The data mining algorithm reliability can be accessed through analysing how they create the data models from a given data. The algorithms are reliable because of the study of specific trends about a given data. The obtained result about the trend helps in identifying the optimal parameters required for the creation of data mining models. The presented optimal parameters helps in deducting appropriate patterns and statistics required for the given