History of Data Mining
- The term "Data Mining" was introduced in 1990s. Early techniques of identifying patterns in data include Bayes theorem in 1700s and the evolution of regression - 1800s
- Data investigation has progressively been improved with indirect, automatic data processing, and other computer science discoveries such as neural networks, clustering, genetic algorithms in 1950s, decision trees in 1960s , supporting vector machines in 1990s.
Data Mining Origins
- Data mining origins are of three types:
- Classical statistics
- Artificial intelligence
- Machine learning
Classical statistics
- Statistics are the basis of most technology on which data mining is made , like regression analysis , variance , standard distribution, standard variance, discriminatory analysis, cluster analysis, and confidence intervals.
Artificial Intelligence
- A Specific AI Concept was adopted by some high-end commercial products, such as query optimization modules for Relational Database Management System(RDBMS).
Machine Learning
- Machine learning is a combination of AI and statistics. It might be considered as an evolution of AI because it mixes AI heuristics with complex statistical analysis.
- Machine learning checks to enable computer programs to know about data they are studying so programs make a distinct decision based on the characteristics of the data examined.
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