assigning weight for attributes in dataset
Only for certain models.

For example for mlp you have this possibility:

The docs show you the attributes in use.


  Attributes:
  ...
  
  coefs_ : list, length n_layers - 1
  The ith element in the list represents the weight matrix corresponding to > layer i.
  
  intercepts_ : list, length n_layers - 1
  The ith element in the list represents the bias vector corresponding to layer > i + 1.


Just build your classifier clf=MLPClassifier(solver="sgd") and set coefs_ and intercepts_ before calling clf.fit().