Cost function: Difference between revisions

From Computer Science Wiki
No edit summary
No edit summary
Line 8: Line 8:
<iframe width="560" height="315" src="https://www.youtube.com/embed/0twSSFZN9Mc" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/0twSSFZN9Mc" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
</html>
</html>
[[Category:2018 case study]]
[[Category:Student created article]]

Revision as of 09:26, 29 January 2023

Introduction

In machine learning, a cost function is a function that is used to optimize a model's parameters by minimizing the error between the predicted output and the actual output. The cost function is used in training a machine learning model to find the set of parameters that minimizes the error between the predicted output and the actual output. The cost function is typically defined as a function of the model's parameters and the training data, and it is used to guide the optimization process by providing a measure of how well the model is doing on the training data.

A fairly decent video