System
Data mining is the process of discovering patterns in large datasets, involving methods at the intersection of machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science. The overall goal of the data mining process is to extract information from a dataset and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data preprocessing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.
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- Transformations: Transformations refer to the process of converting raw data into a more useful format for analysis. This involves cleaning, aggregating, and manipulating data to create new variables or features that can be used to build models or gain insi ... Read More >>
- Hierarchical Data Structure: In the context of data science, a hierarchical data structure refers to a way of organizing and representing data in a hierarchical or tree-like format. This structure consists of nodes that are connected by parent-child relationships, wher ... Read More >>
- Statistical Metric: A statistical metric is a quantitative measure that is used to assess, compare, and analyze data. It is a mathematical function that is applied to a set of data to provide information about its characteristics. Statistical metrics are used ... Read More >>
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