def prepare_classify_mode(dataset_name, current_patient_name):
fc.candidatesDataFile = neuro_networks_path + "candidates_" + current_patient_name + ".csv"
fc.neuroNetworkFile = neuro_networks_path + "network_" + dataset_name + ".xml"
fc.reportDataFile = neuro_networks_path + "report_" + dataset_name + ".txt"
fc.bestNetworkFile = neuro_networks_path + "best_nn_" + dataset_name + ".xml"
fc.bestNetworkInfoFile = neuro_networks_path + "best_nn_" + dataset_name + ".txt"
fc.sepSymbol = ","
fc.showExpected = False
#SetLevel("DEBUG")
SetLevel("ERROR")
def prepare_learning_mode(dataset_name):
fc.ethalonsDataFile = neuro_networks_path + "ethalons_" + dataset_name + ".csv"
fc.neuroNetworkFile = neuro_networks_path + "network_" + dataset_name + ".xml"
fc.reportDataFile = neuro_networks_path + "report_" + dataset_name + ".txt"
fc.bestNetworkFile = neuro_networks_path + "best_nn_" + dataset_name + ".xml"
fc.bestNetworkInfoFile = neuro_networks_path + "best_nn_" + dataset_name + ".txt"
fc.sepSymbol = ","
fc.showExpected = True
#SetLevel("DEBUG")
SetLevel("ERROR")
def classify():
fc.reportDataFile = "report.txt"
fc.sepSymbol = ","
fc.showExpected = True
SetLevel("DEBUG")
parameters = {
"config": str(num_columns) + ",3,2,1",
"epochs": 100,
"rate": 0.5,
"momentum": 0.5,
"epsilon": 0.05,
"stop": 1
}
fc.Main(classifyParameters=parameters)
def train_classifier():
fc.ethalonsDataFile = "ethalons.dat"
fc.candidatesDataFile = "candidates.dat"
fc.neuroNetworkFile = "network.xml"
fc.sepSymbol = ","
SetLevel("DEBUG")
parameters = {
"config": str(num_columns) + ",3,2,1",
"epochs": 100,
"rate": 0.5,
"momentum": 0.5,
"epsilon": 0.05,
"stop": 1
}
fc.Main(learnParameters=parameters)
replace_with = float(data[column].sum()) / data.shape[0]
data[column].fillna(replace_with, inplace=True)
data.to_csv(resource_path + "without_nan.csv")
train, test = train_test_split(data, test_size=0.3, random_state=0)
#test["Class"].replace({0: "", 1: ""}, inplace=True)
train.to_csv("ethalons.dat", index=False)
test.to_csv("candidates.dat", index=False)
fc.EthalonDataFile = "ethalons.dat"
fc.candidatesDataFile = "candidates.dat"
fc.neuroNetworkFile = "network.xml"
fc.sepSymbol = ","
SetLevel("DEBUG")
parameters = {
"config": str(num_columns) + ",3,2,1",
"epochs": 120,
"rate": 0.6,
"momentum": 0.38,
"epsilon": 0.044,
"stop": 1}
fc.Main(learnParameters=parameters)
fc.reportDataFile = "report.txt"
fc.sepSymbol = ","
fc.showExpected = True
SetLevel("DEBUG")
parameters = {