There are some basic data mining tasks such as association. The universal method is an idealistic fantasy. We should know that there is no single method which is appropriate for all possible problems. Data Mining - Tasks Introduction Data Mining deals with what kind of patterns can be mined. The structural level of the model specifies (often graphically) which variables are locally dependent on each other, and Data Mining Tasks Using data mining task depends on the application domain and the structure of the patterns that are expected to be extracted.We would attempt to create a model that can predict the continuous value of the stock. (f) Predicting the future stock price of a company using historical records. Dependency Modeling consists of finding a model which describes significant dependencies between variables. However, in this specic case, solu-tions to thisproblemwere developed bymathematicians a long timeago,andthus,wewouldn’tconsiderittobedatamining.Summarization involves methods for finding a compact description for a subset of data.Closely related to clustering is the task of probability density estimation which consists of techniques for estimating,įrom data, the joint multi-variate probability density function of all of the variables/fields in the database.Clustering is a common descriptive task where one seeks to identify a finite set of categories or clusters to describe the data.Regression is learning a function which maps a data item to a real-valued prediction variable.Data mining, an essential process where intelligent and efficient methods are. Classification is learning a function that maps (classifies) a data item into one of several predefined classes. In this today’s generation enormous amount of data stored in databases and data warehouses, for analysis the stored data for business intelligence to decision making, becomes difficult. Data selection, where data relevant to the analysis task are retrieved.The goals of prediction and description are achieved by using the following primary data mining tasks: Prediction is often the primary goal of the KDD process. Data Mining refers to the mining or discovery of new information in terms of. This is in contrast to pattern recognition and machine learning applications (such as speech recognition) where This paper deals with detail study of Data Mining its techniques, tasks and related Tools. However, in the context of KDD, description tends to be more important than prediction. The relative importance of prediction and description for particular data mining applications can vary considerably. Description focuses on finding human-interpretable patterns describing the data.Prediction involves using some variables or fields in the database to predict unknown or future values of other variables of interest.
The two "high-level" primary goals of data mining, in practice, are prediction and description.
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