Principal Component Analysis of Process Datasets with Missing Values
Datasets with missing values arising from causes such as sensor failure, inconsistent sampling rates, and merging data from different systems are common in the process industry. Methods for handling missing data typically operate during data pre-processing, but can also occur during model building....
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020
|
| Online Access: | https://hdl.handle.net/1721.1/125630 |