Max Features

Change the number of features, or things to look for, in your classifier model

Written by Raul Garreta
Updated over a week ago

Max features sets the maximum number of features to be used to characterize texts in the training/classification process. This number affects how many computation resources are needed to train the model. More features means more computation time is necessary. Also, the amount of time needed to classify new texts is affected.

Intuitively, adding more features should improve results, but this is not always the case, adding more features could decrease accuracy (as well as increase computation time).

The default value is set in 10,000 features which is a reasonable value for text mining applications. More features may allow better representation of the model, but too many may have the risk of overfitting the data, and decrease the generalization performance.

Try different max features to see what affect it has on your classifier performance.

Did this answer your question?