for train_index, test_index in rskf.split(X, y):
X_train, X_test = X.iloc[train_index], X.iloc[test_index]
y_train, y_test = le.fit_transform(y.iloc[train_index]),le.transform(y.iloc[test_index])
HC_clusters, acc, je = Methods.heirachical_clustering(X_train,y_train, X_test, y_test, Nc)
HC_['acc'].append(acc)
HC_['je'].append(je)
gc.collect()
Kmeans_clusters, acc, je = Methods.start_Kmeans(X_train,y_train, X_test, y_test,Nc, trueLabel,itt,sValue)
Kmeans_['acc'].append(acc)
Kmeans_['je'].append(je)
gc.collect()
acc, je = Methods.start_PSO(X_train, X_test, y_train, y_test,Nc,NParticles, itt)
PSO_['acc'].append(acc)
PSO_['je'].append(je)
gc.collect()
HC_Kmeans_clusters, acc, je = Methods.HC_Kmeans(X_train,X_test,y_train,y_test,Nc,HC_clusters,itt,sValue)
HC_Kmeans_['acc'].append(acc)
HC_Kmeans_['je'].append(je)
gc.collect()
acc, je = Methods.Hybrid_PSO(X_train,X_test,y_train,y_test,Nc,Kmeans_clusters,NParticles, itt)
Kmeans_PSO_['acc'].append(acc)
Kmeans_PSO_['je'].append(je)
gc.collect()
acc, je = Methods.Hybrid_PSO(X_train,X_test,y_train,y_test,Nc,HC_clusters,NParticles, itt)
HC_PSO_['acc'].append(acc)
HC_PSO_['je'].append(je)
gc.collect()
acc, je = Methods.Hybrid_PSO(X_train,X_test,y_train,y_test,Nc,HC_Kmeans_clusters,NParticles, itt)
HC_Kmeans_PSO_['acc'].append(acc)
HC_Kmeans_PSO_['je'].append(je)
gc.collect()
