dataset = pd.get_dummies(pd.read_csv("AlzheimerDisease.csv",delimiter=","))
datasetDiagnosis = pd.get_dummies(pd.read_csv("AlzheimerDiseaseD.csv",delimiter=","))
X = dataset.iloc[:, :].values
y = datasetDiagnosis.iloc[:, -1].values
Label = pd.value_counts(y).to_frame().reset_index()
print(Label)
# SVM Models
ModelLinear = SVM(X, y)
ModelLinear.Linearparam()
df1_confmat, df1_f1_micro, df1_f1_macro, df1_accuracy, df1_MCC = ModelLinear.training("SVMLinear", ModelLinear.C)
ModelRBF = SVM(X, y)
ModelRBF.RBFparam()
df2_confmat, df2_f1_micro, df2_f1_macro, df2_accuracy, df2_MCC = ModelRBF.training("RBF", ModelRBF.C, ModelRBF.gamma)
#ANN models
ModelANN = ANN(X, y, Label)
ModelANN.Tune()
df3_confmat, df3_f1_micro, df3_f1_macro, df3_accuracy, df3_MCC = ModelANN.Train(ModelANN.batch, ModelANN.dropout1, ModelANN.dropout2, ModelANN.epochs)
# Others
