-Improved dataset random split

-Early stop if accuracy get above certain value (train)
-I didnt add the full dataset to the git to keep it lightweight (i will be adding download links)

Author: aferral

runExp.py

@@ -9,15 +9,15 @@
     os.makedirs(outReport)
 
 
-datasets = ["MFPT32","MFPT96","CWRbearings",'MFPTFFT32','MFPTFFT96']
+# datasets = ["MFPT32","MFPT96","CWRbearings",'MFPTFFT32','MFPTFFT96']
 
-# dataset =["CW32Scalograms"
-# "CW32Spectrograms",
-# "CW96Scalograms",
-# "MFPT32Scalograms",
-# "MFPT32Spectrograms",
-# "MFPT96Scalograms",
-# "MFPT96Spectrogram"]
+datasets =["CW32Scalograms"
+"CW32Spectrograms",
+"CW96Scalograms",
+"MFPT32Scalograms",
+"MFPT32Spectrograms",
+"MFPT96Scalograms",
+"MFPT96Spectrogram"]
 
 
 
@@ -28,7 +28,7 @@
         alt = int(i)
 
         now = time.strftime('-day%Y-%m-%d-time%H-%M')
-        nb_kwargs = {'dataFolder': dFolder, 'alternativeArc': alt, 'timeNow': now, 'epochs' : 1}
+        nb_kwargs = {'dataFolder': dFolder, 'alternativeArc': alt, 'timeNow': now, 'epochs' : 20}
 
         dname = nb_kwargs['dataFolder'].split("/")[1]
         alt2 = str(nb_kwargs['alternativeArc'])