- knowledge classification
- library classification
- archival classification

Types of Classification

The population error (or true error) of a classifier $$f$$, denoted as $$\epsilon(f)$$, is the expected fraction of examples in the entire underlying population for which the classifier makes an incorrect prediction. Given a probability density function $$p(\mathbf{x}, y)$$ for the true data distribution $$P$$, it is calculated as the expectation of the error indicator variable:
$$\epsilon(f) = E_{(\mathbf{x}, y) \sim P} \mathbf{1}(f(\mathbf{x}) 
eq y) = \int\int \mathbf{1}(f(\mathbf{x}) 
eq y) p(\mathbf{x}, y) \;d\mathbf{x} dy$$

Population Error of a Classifier

The sorting of things (concrete and abstract) into groups on the basis of one or more characteristics.

Georgetown University

Google

- Logical reasoning
- Valid and sound arguments
- Formal system of logic
- Classification

Concepts in logic

Satija, M.P.. (2000). Library classification: An essay in terminology. Knowledge Organization. 27. 221-229. 

Library classification: An essay in terminology

https://openstax.org/details/books/microbiology/

Microbiology covers the scope and sequence requirements for a single-semester microbiology course for non-majors. The book presents the core concepts of microbiology with a focus on applications for careers in allied health. The pedagogical features of the text make the material interesting and accessible while maintaining the career-application focus and scientific rigor inherent in the subject matter. Microbiology’s art program enhances students’ understanding of concepts through clear and effective illustrations, diagrams, and photographs.

Microbiology is produced through a collaborative publishing agreement between OpenStax and the American Society for Microbiology Press. The book aligns with the curriculum guidelines of the American Society for Microbiology.

Learn Before

Related

Learn After