Timeline for Data normalization of count data for neural networks
Current License: CC BY-SA 4.0
2 events
| when toggle format | what | by | license | comment | |
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| Aug 16, 2023 at 10:59 | comment | added | AlexSC | I like this idea, specially if you have an expected top count. If you divide your counts for the expected top count, you convert your input in universal rates, that do not depend on the samples you have. It´s the same when you divide pixel values by 255 before inputing them to a convolutional NN. | |
| Jun 19, 2021 at 15:58 | history | answered | Brian Spiering | CC BY-SA 4.0 |