Abstract
Predictive modeling can be defined as modeling the historical data using statistical and machine learning techniques to predict future observations. Prediction modeling tasks can be grouped into three categories: supervised learning, unsupervised learning and reinforcement learning.
| Original language | English |
|---|---|
| Title of host publication | Springer Series in Advanced Manufacturing |
| Publisher | Springer Nature |
| Pages | 49-112 |
| Number of pages | 64 |
| DOIs | |
| Publication status | Published - 2022 |
Publication series
| Name | Springer Series in Advanced Manufacturing |
|---|---|
| ISSN (Print) | 1860-5168 |
| ISSN (Electronic) | 2196-1735 |
Bibliographical note
Publisher Copyright:© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.