module metrics.regression_custom

Short summary

module lightmlboard.metrics.regression_custom

Metrics about regressions.

source on GitHub

Functions

function truncated documentation
l1_reg_max Implements a L1 scoring function which does not consider error above threshold max_val.

Documentation

Metrics about regressions.

source on GitHub

lightmlboard.metrics.regression_custom.l1_reg_max(exp, val, max_val=180, nomax=False, exc=True)[source]

Implements a L1 scoring function which does not consider error above threshold max_val.

Parameters:
  • exp – list of values or numpy.array
  • val – list of values or numpy.array
  • max_val – every value above max_val is replaced by max_val before computing the differences
  • nomax – removes every value equal or above nomax in expected set, then compute the score
  • raises – an exception if not enough submitted items
Returns:

score

If ``max_val==180`, the function computes:

E = \frac{1}{n} \sum_{i=1}^n \frac{\left| \min (Y_i, 180) - \min(f(X_i), 180) \right|}{180}

The computation is faster if numpy.array are used (for exp and val). exp and *val can be filenames or streams. In that case, the function expects to find two columns: id, value in both files or streams.

source on GitHub