ea5d191f7f71b6fa927a96ef4e785c762a54d5db,examples/decoding/plot_oasis_vbm_space_net.py,,,#,14

Before Change

////// Fit and predict //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
from nilearn.decoding import SpaceNet
decoder = SpaceNet(memory=memory, screening_percentile=10, verbose=1,
                   mask=nifti_masker, n_jobs=14)

////// Fit and predict
decoder.fit(new_images, age)
coef_niimg = decoder.coef_img_
age_pred = decoder.predict(new_images).ravel()

////// Visualization //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
import matplotlib.pyplot as plt

After Change

import matplotlib.pyplot as plt
from nilearn.plotting import plot_stat_map
for penalty in ["tv-l1", "smooth-lasso"]:
    decoder = SpaceNetRegressor(memory="cache", penalty=penalty, verbose=2)
    decoder.fit(X_train, y_train)  // fit
    coef_img = decoder.coef_img_
    y_pred = decoder.predict(X_test).ravel()  // predict
    mse = np.mean(np.abs(y_test - y_pred))

    ////// Visualization //////////////////////////////////////////////////////////////////////////////////////////////////////////////////
    // weights map
    background_img = X[0]

Instances