Vetting of GA feature subsets

vetting_ga.py

scores = [] 
for i in range(len(report)):
  
  myfeats = report.iloc[i,1] ; print(myfeats)
  X = D[myfeats] ; y = y
  clf = LogisticRegression(solver = "liblinear", C = 6, tol = 1)
  #clf = RandomForestClassifier()
  rskf = RepeatedStratifiedKFold(n_splits = 10, n_repeats = 100)
  score = np.mean(cross_val_score(clf, X, y, cv = rskf, scoring = "roc_auc"))
  scores.append(score) 
  print("Score This Round", score)
print("-------------------")

for i in range(len(scores)):
  if scores[i] == np.max(scores):
    print("Max Score", scores[i]); print("Features:", report.iloc[i,1])