c943318502c17ea9d909e79ce898431282768cb9,plot_poldrack_space_net.py,,,#,6
Before Change
mask_img = nibabel.Nifti1Image(mask.astype(np.int), affine)
X_train = nibabel.Nifti1Image(img_data[:, :, :, :n_samples_train], affine)
y_train = y[:n_samples_train]
X_test = nibabel.Nifti1Image(img_data[:, :, :, n_samples_train:], affine)
y_test = y[n_samples_train:]
////// Fit and predict ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
After Change
////// Load data ////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
from nilearn.datasets import fetch_mixed_gambles
mem = Memory(cachedir="cache", verbose=3)
data = mem.cache(fetch_mixed_gambles)("data/Jimura_Poldrack_2012_zmaps",
n_subjects=16, make_Xy=True)
X, y, mask_img = data.X, data.y, data.mask_img
// prepare input data for learner
n_samples = len(X)
n_samples_train = n_samples * 8 / 10
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances
Project Name: nilearn/nilearn
Commit Name: c943318502c17ea9d909e79ce898431282768cb9
Time: 2015-07-28
Author: elvis.dohmatob@inria.fr
File Name: plot_poldrack_space_net.py
Class Name:
Method Name:
Project Name: mortendahl/tf-encrypted
Commit Name: 2ee326e21cd8559c077cef408d32355d56484bb1
Time: 2018-10-10
Author: 1278248+morgangiraud@users.noreply.github.com
File Name: examples/mnist/run.py
Class Name:
Method Name:
Project Name: nilearn/nilearn
Commit Name: 07bbcbb72cbfcea9ef10087167163138165c5003
Time: 2015-07-28
Author: elvis.dohmatob@inria.fr
File Name: plot_poldrack_space_net.py
Class Name:
Method Name: