Ejemplo n.º 1
0

XTrainTransf = dataset.XTrainTransf
XTestTransf = dataset.XTestTransf

lambda_opt = {"alpha": 67.1590893061}

#model_list = {ISTA(), FISTA(), Shooting(), ADMM()}
model_list = {modifiedShooting(DistanceCorrelation())}
ext_data = ".npz"
ext_model = ".pkl"
folder = "AlgorithmResults/"

for model in model_list:
    lasso = LASSOEstimator(model)
    lasso.set_params(**lambda_opt)
    lasso.fit(XTrainTransf,YTrain)

    y_pred_test = lasso.predict(XTestTransf)
    mse_test = mean_squared_error(YTest, y_pred_test)
    print ("mse_test "+model.__class__.__name__,mse_test)

    y_pred_train = lasso.predict(XTrainTransf)
    mse_train = mean_squared_error(YTrain, y_pred_train)

    print("mse_train "+model.__class__.__name__,mse_train)

    np.savez(folder+model.__class__.__name__+ext_data, XTrain=XTrain, YTrain = YTrain, mse_test=mse_test, XTest=dataset.XTest, YTest = YTest, y_pred_test=y_pred_test,
         XTrainTransf=XTrainTransf, XTestTransf=XTestTransf, mse_train = mse_train)

    joblib.dump(lasso, folder+model.__class__.__name__+'_model'+ext_model, compress=9)