Data Science for Genomics 2023
DOI: 10.1016/b978-0-323-98352-5.00011-2
|View full text |Cite
|
Sign up to set email alerts
|

One step to enhancement the performance of XGBoost through GSK for prediction ethanol, ethylene, ammonia, acetaldehyde, acetone, and toluene

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
0
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 20 publications
0
0
0
Order By: Relevance
“…The technique assesses using a variety of perspectives. RE generation forecasting method present by [21] based on pre-processing step using Bayesian probabilistic technique with Bidirectional Long Short-Term Memory (BLSTM), also using vibrational Autoencoder (VAE)to overcome the high complexities that causes by Bayesian deep learning technique where it requires high computations to deal with large probability distributions. Model efficiency was evaluated by using comparative analysis (time complexity, forecasting error), pinball loss, RMSE, reconstruction error and other metrics but not considered the surpluses energy.…”
Section: Evaluation Challengesmentioning
confidence: 99%
“…The technique assesses using a variety of perspectives. RE generation forecasting method present by [21] based on pre-processing step using Bayesian probabilistic technique with Bidirectional Long Short-Term Memory (BLSTM), also using vibrational Autoencoder (VAE)to overcome the high complexities that causes by Bayesian deep learning technique where it requires high computations to deal with large probability distributions. Model efficiency was evaluated by using comparative analysis (time complexity, forecasting error), pinball loss, RMSE, reconstruction error and other metrics but not considered the surpluses energy.…”
Section: Evaluation Challengesmentioning
confidence: 99%