Performance Comparison of New Adjusted Min-Max with Decimal Scaling and Statistical Column Normalization Methods for Artificial Neural Network Classification
In this research, the normalization performance of the proposed adjusted min-max methods was compared to the normalization performance of statistical column, decimal scaling, adjusted decimal scaling, and min-max methods, in terms of accuracy and mean square error of the final classification outcome...
Saved in:
| Main Author: | Saichon Sinsomboonthong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
|
| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/2022/3584406 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Efficiency Comparison of New Adjusted Nonparametric and Parametric Statistics Interval Estimation Methods in the Simple Linear Regression Model
by: Saichon Sinsomboonthong, et al.
Published: (2022-01-01) -
New adjusted missing value imputation in multiple regression with simple random sampling and rank set sampling methods.
by: Juthaphorn Sinsomboonthong, et al.
Published: (2025-01-01) -
Digit recognition using decimal coding and artificial neural network
by: Toufik Datsi, et al.
Published: (2021-12-01) -
Dewey Decimal Classification(DDC)
by: Birger Hjørland
Published: (2025-04-01) -
The backtrack Hölder gradient method with application to min-max and min-min problems
by: Bolte, Jérôme, et al.
Published: (2023-12-01)