Generate result tables for cv_tt mode

Functions for making result tables specifically for the CV_TT type of experiments.

In CV_TT experiments, the following is done

1. Labels ‘y_train’ are expected to exist, with ‘y_train_true’ and ‘y_train_pred’ columns. This must be the true y in the first column, and in the second column the predicted values of y when these indices were in the hold-out fold of cross validation.

2. Labels ‘y_test’ are expected to exist, with ‘y_test_true’ and ‘y_test_pred’. These columns are the true and predicted values of y on the test dataset. Predicted values should (theoretically) be made by training the model on the full training dataset, and predicting the test dataset.

3. Tables are created for each possible metric/metric combination of the metrics in the configuration file. In the tables, each method is given in a single column. In each cell, the performance on the test dataset as measured by the second metric is shown for the parameter configuration for which the performance on the first metric is optimal. This is done for all metric targets other than ‘y_train’.

abed.results.cv_tt.cvtt_build_tables_metric(abed_cache, train_metric, test_metric, target)

abed.results.cv_tt.cvtt_make_tables_metric(abed_cache, train_metric, test_metric, target)

abed.results.cv_tt.cvtt_tables(abed_cache)

abed.results.cv_tt.filter_targets(targets)