![]() This knowledge about the domain to be mined is useful for guiding the knowledge discovery process and evaluating the patterns found. The background knowledge to be used in the discovery process This specifies the data mining functions to be performed, such as characterization, discrimination, association or correlation analysis, classification, prediction, clustering, outlier analysis, or evolution analysis.ģ. Since virtual relations are called Views in the field of databases, the set of task-relevant data for data mining is called a minable view. This initial relation may or may not correspond to physical relation in the database. This data retrieval can be thought of as a subtask of the data mining task. The initial data relation can be ordered or grouped according to the conditions specified in the query. The data collection process results in a new data relational called the initial data relation. In a relational database, the set of task-relevant data can be collected via a relational query involving operations like selection, projection, join, and aggregation. This includes the database attributes or data warehouse dimensions of interest (the relevant attributes or dimensions). This specifies the portions of the database or the set of data in which the user is interested. The set of task-relevant data to be mined List of Data Mining Task PrimitivesĪ data mining query is defined in terms of the following primitives, such as:ġ. This facilitates a data mining system's communication with other information systems and integrates with the overall information processing environment. The design of an effective data mining query language requires a deep understanding of the power, limitation, and underlying mechanisms of the various kinds of data mining tasks. Having a data mining query language provides a foundation on which user-friendly graphical interfaces can be built.ĭesigning a comprehensive data mining language is challenging because data mining covers a wide spectrum of tasks, from data characterization to evolution analysis. Representation for visualizing the discovered patterns.Ī data mining query language can be designed to incorporate these primitives, allowing users to interact with data mining systems flexibly.Interestingness measures and thresholds for pattern evaluation.Background knowledge to be used in the discovery process.The data mining primitives specify the following, These primitives allow the user to interactively communicate with the data mining system during discovery to direct the mining process or examine the findings from different angles or depths. ![]() A data mining query is defined in terms of data mining task primitives. Next → ← prev Data Mining Task PrimitivesĪ data mining task can be specified in the form of a data mining query, which is input to the data mining system. ![]()
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