The ETH model issued 4 trades in April locking in +36%, which is pretty exceptional. It has sat out for this last upswing, but I assume it’s looking for confirmation to break above these levels. We want to get most of the upswings and minimize losses on the downswings.
In terms of precision, that is referencing R-Squared, which measures the amount of error removed by the model. We use that measure because it correlates very well with how our models do once their output is handed off to the trading system.
It will never hit 1. And each incremental improvement is going to be much more challenging to achieve.
Here’s a link to read more: https://crypto-ml.com/blog/machine-learning-upgrade-to-5-0-deep-neural-networks/#R-Squared
And an image that shows why we use it as one of our main measures:
From the post…
By doubling the R-Squared value, we were able to achieve results 79 times better.
The following chart shows the difference between the 4.x and 5.0 models. By using Deep Neural Networks, we are making a large jump in precision.
- This reply was modified 2 months ago by Justin.