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Research Anthology on Machine Learning Techniques, Methods, and Applications

Classification and Machine Learning

Damian Alberto

Published May 13, 2022Read PDF ↗View on arXiv ↗

Abstract

The manual classification of a large amount of textual materials are very costly in time and personnel. For this reason, a lot of research has been devoted to the problem of automatic classification and work on the subject dates from 1960. A lot of text classification software has appeared. For some tasks, automatic classifiers perform almost as well as humans, but for others, the gap is still large. These systems are directly related to machine learning. It aims to achieve tasks normally affordable only by humans. There are generally two types of learning: learning “by heart,” which consists of storing information as is, and learning generalization, where we learn from examples. In this chapter, the authors address the classification concept in detail and how to solve different classification problems using different machine learning techniques.

Sourced from arXiv · Updated September 2, 2026

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FAQ

Common questions

What is "Classification and Machine Learning" about?

The manual classification of a large amount of textual materials are very costly in time and personnel. For this reason, a lot of research has been devoted to the problem of automatic classification and work on the subject dates from 1960. A lot of text classification software ha

Who wrote this paper?

Damian Alberto

Where can I read the full paper?

The full text is available as a PDF on arXiv (linked above), published May 13, 2022.

Does this paper have a DOI?

Yes: 10.4018/978-1-6684-6291-1.ch004.