Feature selection

Concept and definition

Feature selection

What is Feature selection?

Feature selection is a process of selecting relevant and informative variables for a machine learning model, with the aim of improving the accuracy and generalisability of the model. Instead of using all available variables, the most relevant features are selected to reduce computational cost and improve model interpretation. Feature selection techniques include statistical, correlation and feature importance methods, among others. It is a technique commonly used in data pre-processing for machine learning.

« Back to glossary

Do you want to get in touch?

CDRs contain data that a telecommunications company collects about phone calls, such as time and length of call. This data can be used in analytical applications.
Fill the form
Share:
Artificial Intelligence Regulatory Compliance

AI technologies are currently being used in companies to transform business processes, boost customer interaction and improve customer service.

Read More »
What is Artificial Intelligence doing today for the financial sector?

The Official Chamber of Commerce of Seville, in collaboration with the Spanish Institute of Financial Analysts (IEAF), offered last March 16th [...]

Read More »
What is Digital Transformation?

What is Digital Transformation? The industrial revolution profoundly changed the society of the 19th century, but the digital transformation of the [...]

Read More »
How does semantic technology work?�

To know how semantic technology works, the first thing you need to know is that it is responsible for helping artificial intelligence systems [...]

Read More »
See more entries
© Gamco 2021, All Rights Reserved - Legal notice - Privacy - Cookies