Firstly, I apologize in advance if the following questions I have are very
basic. I am very new to coding in general, as well as Principal Component
Analysis and scikit-learn. I am trying to finish a project for an internship
and hit a wall, and am desperately trying to seek help to solve this b
I have a script to classify MRI perfusion maps from healthy subjects and
patients. For the file IO and the classifier I have started with the
example code in Abraham et al 2014 [https://arxiv.org/pdf/1412.3919.pdf].
I use the same classifier as in the paper to produce a back-projected map
of class
On 05/03/2017 08:05 AM, 熊瑶 wrote:
Dear professor,
scikit-learn is really good for me to do some work using machine
learning method. Here, I have two questions:
1）To do 5 fold cross-validation, when I use StratifiedKFold，I could
get stratified folds that each fold contains approximately the
Hi Alle,
I think that what has changed between 2014 and today is that the
coefficients coef are now a 2D array (number of hyperplanes x number of
features). In your case, the first direction is of length one, so you
could just do:
coef = clf.coef_[0]
and your script should work.
The code of the
