rfloocv3.py

# Train data - all other people in dataframe
data_train = data_filtered.drop(columns=dropcols)
X_train = data_train.drop(columns=[outcomevar])
feature_list = list(X_train.columns) #Get a feature list to use for importances later on

X_train= np.array(X_train) #Re-format as numpy array for input into model
y_train = np.array(data_train[outcomevar]) #Outcome variable here