core(metrics): update lantern coefficients

[patrickhulce]

This PR updates the lantern coefficients to the values that offer the lowest absolute error of the 9-run accuracy/variance dataset, they haven't ever been updated so the jump is expected. this PR also turns on the flexibleOrdering feature for the optimistic estimate which improved accuracy ~5% on FCP/FMP 🎉

In the ideal case if lantern were perfect, we would expect the optimistic/pessimistic coefficients to both be positive, sum to ~1, and the intercept to be 0. The good news is we've made considerable progress toward this goal for FCP/FMP, intercepts are significantly lower and coefficients are positive and sum to ~1.

Progress is positive on TTI, the coefficients now sum to ~1 instead of ~1.5 and the intercept is roughly the same.

Speed Index is just weird, the optimistic estimate being real speed index throws things off quite a bit. The lowest absolute error is coefficients at ~2x and then a negative intercept. This actually doesn't seem that bad since on the low end we'll be using the FCP estimate for speed index anyhow, and if it improves accuracy on the high end of speed index, we'll take it, but still not an ideal situation.

MAPE State of the World

Aside: once I add the GCP test suite I think we should shift away from measuring based on MAPE and do the search approach, % of results that are Good/OK/Terrible which is much easier to interpret and judge success

Metric	MAPE	MAPE on middle 50%
FCP	24.4%	9.8%
FMP	27.4%	11.0%
FCPUI	29.9%	16.2%
TTI	30.9%	16.1%
SI	39.6%	18.7%

[brendankenny]

This is all great, and important to get in for first users of 3.0. LGTM!

we should shift away from measuring based on MAPE and do the search approach, % of results that are Good/OK/Terrible which is much easier to interpret and judge success

distribution of residuals 4eva