o6 = Classification.MLP(2,32)
o7 = Classification.ABC(2,32)
o8 = Classification.GNB(2,32)
o9 = Classification.QDA(2,32)
o10 = Classification.SGD(2,32)
o11= NNC.NNC(2,32)
df30 = pd.DataFrame(data = {"LogReg": o1, "SVM": o2, "DTC": o3, "KNC": o4, "RFC": o5,"MLP": o6,
"ABC": o7, "GNB": o8, "QDA": o9, "SGD": o10, "NNC":o11}, index = [".9", ".8", ".5", ".25"])
print(df30)
#%%
Plotting.SVCPlot(2,4)
#%%
Plotting.DTCPlot(2,32)
#%%
Plotting.Histo()
#%%
print ("10 best features")
p1 = Classification.LogReg10()
p2 = Classification.SVM10()
p3 = Classification.DTC10()
p4 = Classification.KNC10()
p5 = Classification.RFC10()
p6 = Classification.MLP10()
p7 = Classification.ABC10()
p8 = Classification.GNB10()
p9 = Classification.QDA10()
