The Overfitting Challenge in Blockchain Analysis

In the context of blockchain analysis, the bias-variance friction is present everywhere. Let's go back to our algorithm that attempts to predict price with a number of blockchain factors. If we use a simple linear regression method, the model is likely to underfit. However, if we use a super complex neural network with a small dataset, the model is likely to overfit. Using machine learning to analyze blockchain data is a very nascent space. As a result, most of the models are encountering the traditional challenges with machine learning applications. Overfitting is one of those omnipresent challenges in blockchain analysis fundamentally due to the lack of labeled data and trained models. There is no magic solution to fight overfitting but some of the principles outlined in this article have proven to be effective for us at IntoTheBlock.