'rrun')
rrun_aucs.append(rrun_mean_auc)
print('After this run with %s followed by %s (γ = %s), mean auc is %s' %
(rrun_kpca, rrun_model, opt_gamma, rrun_mean_auc[0][0]))
print("\n%.2f seconds elapsed so far\n" % (time.time() - StartTime))
print(
'\n###################################################################\n'
)
print('rrun_aucs:')
print(rrun_aucs[0][0])
p2f.mpl_simplebar(rds_labels,
rrun_aucs[0][0],
'Target outcome',
'Mean AUC',
p2f.get_col_list('autumn', len(rds_labels)),
output='save',
path='%s%s_summarybars.png' % (filepath, nowtime))
p2f.js_bars(rds_labels, rrun_aucs[0][0],
'%s%s_summarybars.js' % (plotpath, nowtime))
print("\n!!! SUCCESSFUL RUN !!!\n")
#Calculate and display time taken or script to run
print("\nTime taken for script to run is %.2f seconds\n" %
(time.time() - StartTime))
X_imp = p2f.filt_imp(inp_df, 0.1)
X, y = p2f.tsplit(X_imp)
rrun_mean_auc, rrun_kpca, rrun_model = p2f.m_run5_3(
X, y, opt_gamma, opt_kpca, opt_model, dataset, filepath, plotpath,
'rrun')
rrun_aucs.append(rrun_mean_auc)
print('After this run with %s followed by %s (γ = %s), mean auc is %s' %
(rrun_kpca, rrun_model, opt_gamma, rrun_mean_auc[0][0]))
print("\n%.2f seconds elapsed so far\n" % (time.time() - StartTime))
print(
'\n###################################################################\n'
)
print('rrun_aucs:')
print(rrun_aucs[0][0])
p2f.mpl_simplebar(rds_labels,
rrun_aucs[0][0],
'Target outcome',
'Mean AUC',
p2f.get_col_list('autumn', len(rds_labels)),
output='show')
#Calculate and display time taken or script to run
print("\nTime taken for script to run is %.2f seconds\n" %
(time.time() - StartTime))