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Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...
It exists, however, in many variations on this theme, such as the Cross-industry standard process for data mining (CRISP-DM) which defines six phases: Business understanding; Data understanding; Data preparation; Modeling; Evaluation; Deployment; or a simplified process such as (1) Pre-processing, (2) Data Mining, and (3) Results Validation.
Typically, users hand over the data transformation task to developers who have the necessary coding or technical skills to define the transformations and execute them on the data. [8] This process leaves the bulk of the work of defining the required transformations to the developer, which often in turn do not have the same domain knowledge as ...
Data processing is the collection and manipulation of digital data to produce meaningful information. [1] Data processing is a form of information processing , which is the modification (processing) of information in any manner detectable by an observer.
Most preprocessors are specific to a particular data processing task (e.g., compiling the C language). A preprocessor may be promoted as being general purpose, meaning that it is not aimed at a specific usage or programming language, and is intended to be used for a wide variety of text processing tasks.
In psychology and cognitive neuroscience, pattern recognition is a cognitive process that matches information from a stimulus with information retrieved from memory. [1]Pattern recognition occurs when information from the environment is received and entered into short-term memory, causing automatic activation of a specific content of long-term memory.
Preprocessing can refer to the following topics in computer science: Preprocessor , a program that processes its input data to produce output that is used as input to another program like a compiler Data pre-processing , used in machine learning and data mining to make input data easier to work with
Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines , logistic regression , and artificial neural networks ).