Real-Time Function Prediction

Below is a script that allows for real-time function prediction.

Specifically, it can take in a training set of millions of observations, and an input vector, and immediately return a prediction for any missing data in the input vector.

Running on an iMac, using a training set of 1.5 million vectors, the prediction algorithm had an average run time of .027 seconds per prediction.

Running on a Lenovo laptop, also using a training set of 1.5 million vectors, the prediction algorithm had an average run time of 0.12268 seconds per prediction.

Note that this happens with no training beforehand, which means that the training set can be updated continuously, allowing for real-time prediction.

So if our function is of the form z = f(x,y), then our training set would consist of points over the domain for which the function was evaluated, and our input vector would be a given (x,y) pair within the domain of the function, but outside the training set.

I’ve attached a command line script that demonstrates how to use the algorithm, applying it to a sin curve in three-space (see “9-6-19NOTES”).

Code available here:

https://www.researchgate.net/project/Information-Theory-SEE-PROJECT-LOG/update/5d72d55f3843b0b98262f6f8

Advertisement

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s