def pacfs_classifier(target_names):
print("* Loading PAC Feature Selection Model...")
with open(main.MODELLO_PAC_FS, 'rb') as file:
model_pacfs = pickle.load(file)
print("* Model PAC Feature Selection loaded")
# continually pool for new text to classify
runModel(model_pacfs, main.PACFS_QUEUE, target_names)
def pac_classifier(target_names):
print("* Loading PAC Model...")
with open(main.MODELLO_PAC, 'rb') as file:
model_pac = pickle.load(file)
print("* Model PAC loaded")
# continually pool for new text to classify
runModel(model_pac, main.PAC_QUEUE, target_names)
def svm_classifier(target_names):
print("* Loading SVM Model...")
with open(main.MODELLO_SVM, 'rb') as file:
model_svm=pickle.load(file)
print("* Model SVM loaded")
# continually pool for new text to classify
runModel(model_svm, main.SVM_QUEUE, target_names)
def cnb_classifier(target_names):
print("* Loading CNB Model...")
with open(main.MODELLO_CNB, 'rb') as file:
model_cnb = pickle.load(file)
print("* Model CNB loaded")
# continually pool for new text to classify
runModel(model_cnb, main.CNB_QUEUE, target_names)
def mlp_classifier(target_names):
print("* Loading MLP Model...")
with open(main.MODELLO_MLP, 'rb') as file:
model_mlp = pickle.load(file)
print("* Model MLP loaded")
# continually pool for new text to classify
runModel(model_mlp, main.MLP_QUEUE, target_names)