search

giacbrd / ShallowLearn

An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.
GNU Lesser General Public License v3.0
198 stars 30 forks source link

test time longer than training time in the performance graph #16

Open prakhar2b opened 7 years ago

prakhar2b commented 7 years ago

@giacbrd @tmylk While running this document classification script, the performance graph generated shows training time to be lesser than test time.

But if we look closely, the training time is actually longer than test time for all the classifier. Here is the log

I think this is not the right way to convert the result into a range of (0,1) on the same axis

training_time = np.array(training_time) / np.max(training_time) test_time = np.array(test_time) / np.max(test_time)

giacbrd commented 7 years ago

Hi, yes that way of plotting times is not so nice. Test times are NOT comparable to training times, the bars are plotted independently and relatively to the two types of times.

The code is exactly as in http://scikit-learn.org/stable/auto_examples/text/document_classification_20newsgroups.html , but I may fix it for ShallowLearn