np.array([compute_median_survival_time(mesh_points,
surv_row)
for surv_row in np.exp(-cum_haz)])
cindex = concordance_index(fold_y_val[:, 0],
predicted_medians,
fold_y_val[:, 1])
else:
raise NotImplementedError(
'Unsupported c-index method: %s' % cindex_method)
cindex_scores.append(cindex)
# ---------------------------------------------------------
# compute IPEC score using a few horizon times
#
fold_IPEC_scores = compute_IPEC_scores(
fold_y_train, fold_y_val, mesh_points, surv,
IPEC_horizons)
for idx, IPEC_horizon in enumerate(IPEC_horizons):
IPEC_scores[idx].append(fold_IPEC_scores[IPEC_horizon])
cross_val_cindex = np.mean(cindex_scores)
cross_val_IPEC_scores = {}
for idx, q in enumerate(IPEC_percentiles):
cross_val_IPEC_scores[q] = np.mean(IPEC_scores[idx])
# print('Bandwidth percentile: %5.4f, ' % bandwidth_percentile
# + 'c-index: %5.4f, ' % cross_val_cindex
# + ', '.join(['IPEC (%.2f): %5.4f'
# % (q, cross_val_IPEC_scores[q] / horizon)
# for q, horizon in
# zip(IPEC_percentiles,
# IPEC_horizons)]))
predicted_medians = \
np.array([compute_median_survival_time(mesh_points,
surv_row)
for surv_row in np.exp(-cum_haz)])
test_cindex = concordance_index(y_test[:, 0],
predicted_medians,
y_test[:, 1])
else:
raise NotImplementedError('Unsupported c-index method: %s'
% cindex_method)
# ---------------------------------------------------------------------
# compute IPEC score using a few horizon times
#
test_IPEC_scores = compute_IPEC_scores(y_train, y_test,
mesh_points, surv,
IPEC_horizons)
print('c-index: %5.4f' % test_cindex
+ ', '
+ ', '.join(['IPEC (%.2f): %5.4f'
% (q, test_IPEC_scores[horizon] / horizon)
for q, horizon in
zip(IPEC_percentiles,
IPEC_horizons)]))
csv_writer.writerow([dataset, experiment_idx, 'cox', test_cindex] +
[test_IPEC_scores[horizon] / horizon
for horizon in IPEC_horizons])
print()
print()