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t. e. Data mining is the process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. [1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from ...
A review and critique of data mining process models in 2009 called the CRISP-DM the "de facto standard for developing data mining and knowledge discovery projects." Other reviews of CRISP-DM and data mining process models include Kurgan and Musilek's 2006 review, and Azevedo and Santos' 2008 comparison of CRISP-DM and SEMMA.
Data preprocessing. Data preprocessing can refer to manipulation, filtration or augmentation of data before it is analyzed, [1] and is often an important step in the data mining process. Data collection methods are often loosely controlled, resulting in out-of-range values, impossible data combinations, and missing values, amongst other issues.
SEMMA is an acronym that stands for Sample, Explore, Modify, Model, and Assess. It is a list of sequential steps developed by SAS Institute, one of the largest producers of statistics and business intelligence software. It guides the implementation of data mining applications. [1] Although SEMMA is often considered to be a general data mining ...
Educational data mining ( EDM) is a research field concerned with the application of data mining, machine learning and statistics to information generated from educational settings (e.g., universities and intelligent tutoring systems ). At a high level, the field seeks to develop and improve methods for exploring this data, which often has ...
Crushing, a form of comminution, one of the unit operations of mineral processing. Mineral processing is the process of separating commercially valuable minerals from their ores in the field of extractive metallurgy. [1] Depending on the processes used in each instance, it is often referred to as ore dressing or ore milling .
Data mining. Machine learning and data mining often employ the same methods and overlap significantly, but while machine learning focuses on prediction, based on known properties learned from the training data, data mining focuses on the discovery of (previously) unknown properties in the data (this is the analysis step of knowledge discovery ...
Sequential pattern mining. Sequential pattern mining is a topic of data mining concerned with finding statistically relevant patterns between data examples where the values are delivered in a sequence. [1] [2] It is usually presumed that the values are discrete, and thus time series mining is closely related, but usually considered a different ...
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