nnfee: New Bitcoin Fee Estimation Tool Using Artificial Neural Network

It is sometimes difficult to know which are the fees that apply to each bitcoin transaction in the blockchaub. This is why nnfee is using an artificial neural network that aims to accurately estimate bitcoin fees.

nnfee is a neural network experiment that mimics a biological network’s functioning, and it is able to calculate which are Bitcoin’s fees. This project that has been conducted by u/mess110, a Reddit user. This would be the first experiment that aims to predict bitcoin transaction fees.

The Redditor describes himself as a ‘free software developer’ and ‘bitcoin contributor.’ He used bitcoin block and transaction data between March 2017 and February 2018. The data collected is equal to 115 GB. The user has saved the full and shortened version of each block so as to analyse them.

Then he used a Smartbit’s API for ‘returning all the blocks, transactions, when the transactions was first seen, and when it was confirmed.’ Moreover he has also used Johoe’s Bitcoin Mempool Statistics tracker so as to have relevant mempool information.

The user was able to separate the training into 12 different parts according to each of the 12 months for which he had collected information. Then he decided to clarify that 5% ‘of the transactions from each month were randomly selected to verify the neural network and not used for training.’

The results have been surprising. mess110 was able to predict with 71.8 percent accuracy the bitcoin fee estimation, which according to him is ‘better than random.’

mess110 commented about it:

“In terms of AI, I have experience but I wish I knew more. Someone more specialized in AI could probably suggest a different neural network or layer configuration which would improve the 71% accuracy. I am sort of hoping I get some feedback on this from the community.”

In the future such a network would allow new users to have a smoother experience when using bitcoin because they will know that their transaction will be confirmed at the correct fee.

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