Data mining


Topic | v1 | created by jjones |
Description

Data mining is a process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.The term "data mining" is a misnomer, because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (mining) of data itself.


Relations

subtopic of Computer science

Computer science is the study of computation and information. Computer science deals with theory of c...

uses Orange

Orange is an open-source data visualization, machine learning and data mining toolkit. It features a...

subtopic of Data science

Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and s...


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Resources

treated in Data Mining Concepts and Techniques

Understand the need for analyses of large, complex, information-rich data sets. Identify the goals an...

treated in Hands-on Text Mining and Analytics

This course provides an unique opportunity for you to learn key components of text mining and analyti...

treated in Applied Text Mining in Python

This course will introduce the learner to text mining and text manipulation basics. The course begins...