title: why sklearn.svm.SVC's attribute coef_ has shape = [n_class * (n_class-1) / 2, n_features]?
body: <p>I'm using sklearn.svm.SVC with linear kernel and i want to get the feature importance, so i use the attribute coeff_ which (as explained here: <a href="https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html" rel="nofollow noreferrer">https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html</a>) is an array with the shape [n_class * (n_class-1) / 2, n_features], for example, im my case, i have 10 classes and 54 features, so the shape is [45,54],</p>
  
  <p>Why i get 45 arrays of weights? what is the meaning of each one of these arrays? Beacuse intuitively i would have expected 10 arrays of weights, one for each class</p>