def compare_IRR(): print "Loading model..." try: model = load_from_pickle('pickle/model.pkl') except OSError, IOError: print "Model not found. Initializing training process, this might take some time..." model = initialize_model()
def compare_IRR(): print "Loading model..." try: model = load_from_pickle("pickle/model.pkl") except OSError, IOError: print "Model not found. Initializing training process, this might take some time..." model = initialize_model()
def run_process(): ''' Main process for app, invoked when administrator is at /refresh. Collects, processes and stores data, as well as calculates expected IRR and other metrics for data table and charts. Returns: Loan details to populate data table at /index. numpy array. ''' print "Requesting loan details..." loan_results, loan_details = request_loan_data() print "Inserting results of API request to database..." try: insert_into_mongodb(loan_results, loan_details) except Exception: print "MongoDB error, proceeding to next step..." print "Loading model..." try: model = load_from_pickle('pickle/model.pkl') except OSError, IOError: print "Model not found. Initializing training process, this might take some time..." model = initialize_model()
df_raw = pd.concat((df_3c, df_3b), axis=0) print "Pre-processing data..." df = process_features(df_raw) print "Initializing model..." model = StatusModel(model=RandomForestRegressor, parameters={ 'n_estimators': 100, 'max_depth': 10 }) print "Training model..." try: model = load_from_pickle('pickle/model.pkl') except OSError, IOError: print "Model not found. Training model, this might take some time..." model.train_model(df) dump_to_pickle(model, 'pickle/model.pkl') print "Calculating IRR..." int_rate_dict = { 'A1': 0.0603, 'A2': 0.0649, 'A3': 0.0699, 'A4': 0.0749, 'A5': 0.0819, 'B1': 0.0867, 'B2': 0.0949, 'B3': 0.1049,
df_3c = pd.read_csv("data/LoanStats3c_securev1.csv", header=True).iloc[:-2, :] df_3b = pd.read_csv("data/LoanStats3b_securev1.csv", header=True).iloc[:-2, :] except OSError, IOError: print "Training data not found. Please install from https://www.lendingclub.com/info/download-data.action" df_raw = pd.concat((df_3c, df_3b), axis=0) print "Pre-processing data..." df = process_features(df_raw) print "Initializing model..." model = StatusModel(model=RandomForestRegressor, parameters={"n_estimators": 100, "max_depth": 10}) print "Training model..." try: model = load_from_pickle("pickle/model.pkl") except OSError, IOError: print "Model not found. Training model, this might take some time..." model.train_model(df) dump_to_pickle(model, "pickle/model.pkl") print "Calculating IRR..." int_rate_dict = { "A1": 0.0603, "A2": 0.0649, "A3": 0.0699, "A4": 0.0749, "A5": 0.0819, "B1": 0.0867, "B2": 0.0949, "B3": 0.1049,