# Bolt

This application provides an example XGBRegressor inference generated by [bolt](https://github.com/aedalzotto/bolt)

The `dataset_t` structure provides the dataset to test.
The first fields of the struct are the model input features: `rel_timestamp,hops,size,prod,cons`
The last field if the target variable `latency`.

The inference runs for every entry of the `data` array using the input features in the `dataset_t` struct.
Every model function call returns a predicted latency.
The error is obtained as the difference from the target variable.

The error is squared and accumulated to result in the squared error.
The squared error is divided by the number of entries in the `data` vector to result in the Mean Squared Error (MSE).
The square root of the MSE results in the RMS Error, i.e., how far in average a predicted value is from the correct one.
