I have identified a set of feature_weights and passed that paramter to the clf.fit function to generate my model fit using sklearn. I want to apply that model to new data one epoch at a time using clf.predict but I cannot find any documentation or posts about how to incorporate the same array of feature weights to the clf.predict function and those weights do not appear to be stored in the clf file (feature importance values are however).

I have identified a set of feature_weights and passed that paramter to the clf.fit function to generate my model fit using sklearn. I want to apply that model to new data one epoch at a time using clf.predict but I cannot find any documentation or posts about how to incorporate the same array of feature weights to the clf.predict function and those weights do not appear to be stored in the clf file (feature importance values are however).

I have identified a set of feature_weights and passed that paramter to the clf.fit function to generate my model fit using sklearn. I want to apply that model to new data one epoch at a time using clf.predict but I cannot find any documentation or posts about how to incorporate the same array of feature weights to the clf.predict function and those weights do not appear to be stored in the clf file (feature importance values are however).

I have identified a set of feature_weights and passed that paramter to the clf.predict function to generate my model fit using sklearn. I want to apply that model to new data one epoch at a time using clf.fit but I cannot find any documentation or posts about how to incorporate the same array of feature weights to the clf.fit function and those weights do not appear to be stored in the clf file (feature importance values are however).