Commit b513e647 authored by Leonie Pick's avatar Leonie Pick

Last test run prior to submission.

parent eb9510fe
......@@ -468,8 +468,8 @@
"FeatureIndices, Features = md.Get_Features(Var['Time'],TargetEvents,Var['Reference'],Var['HMC'],HMC11y,HMC1y,dHMC,Var['B_MLT'],Var['ASY'],Save)\n",
"\n",
"#If saved results are available, run the following two lines:\n",
"#FeatureSave = np.load('./Dump/Out/Features.npz')\n",
"#FeatureIndices = FeatureSave['FeatureIndices']; Features = FeatureSave['Features']\n",
"FeatureSave = np.load('./Dump/Out/Features.npz')\n",
"FeatureIndices = FeatureSave['FeatureIndices']; Features = FeatureSave['Features']\n",
"\n",
"md.Get_Diagnostics(Features,TargetEvents,Var['Reference'],Save)"
]
......@@ -667,8 +667,8 @@
" np.savez('./Dump/Out/ModelComp',Score=ScoreAll,Std=StdAll)\n",
"\n",
"#If saved results are available, run the following two lines:\n",
"#ModelComp = np.load('./Dump/Out/ModelComp.npz')\n",
"#ScoreAll = ModelComp['Score']; StdAll = ModelComp['Std']\n",
"ModelComp = np.load('./Dump/Out/ModelComp.npz')\n",
"ScoreAll = ModelComp['Score']; StdAll = ModelComp['Std']\n",
"\n",
"display(pd.DataFrame(data=np.around(ScoreAll[:,11:,0],2), columns=['ACC','LR+','LR-','DOR','F1a','F1b','FB','HSS','MCC','J','Deltap'],index=Estimators)) \n",
"BestEstimator = Estimators[np.argmax(ScoreAll[:,19,0])]\n",
......@@ -1100,9 +1100,9 @@
" joblib.dump(ModelAll,'./Dump/Out/Model.joblib')\n",
"\n",
"#If saved results are available, run the following three lines:\n",
"#ModelAssess = np.load('./Dump/Out/ModelAssess.npz')\n",
"#ScoreAll = ModelAssess['Score']; StdAll = ModelAssess['Std']\n",
"#ModelAll = joblib.load('./Dump/Out/Model.joblib')\n",
"ModelAssess = np.load('./Dump/Out/ModelAssess.npz')\n",
"ScoreAll = ModelAssess['Score']; StdAll = ModelAssess['Std']\n",
"ModelAll = joblib.load('./Dump/Out/Model.joblib')\n",
" \n",
"display(pd.DataFrame(data=np.around(ScoreAll[0,11:,:].T,2), columns=['ACC','LR+','LR-','DOR','F1a','F1b','FB','HSS','MCC','J','Deltap'],index=['Score','Score Training']))\n",
"display(pd.DataFrame(data=np.around(StdAll[0,11:,:].T,3), columns=['ACC','LR+','LR-','DOR','F1a','F1b','FB','HSS','MCC','J','Deltap'],index=['Std','Std Training']))\n",
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