Enhanced Text Classification through various Frequency Weighting proposes the estimation of improving accuracy through implying various weighting strategies in SVM and Maximum Entropy algorithms using Yelp review dataset. Modelled using SVM, Maximum Entropy and various weightings of weighSMART function in R programming. Due to its limitations in build-in function, altered the source code of R package and expanded the new document weights and produced a better accuracy of 79% & 92%.
-
Notifications
You must be signed in to change notification settings - Fork 0
Enhanced Text Classification through various Frequency Weighting proposes the estimation of improving accuracy through implying various weighting strategies in SVM and Maximum Entropy algorithms using Yelp review dataset.
ash-sha/Frequency-Weighting
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
Enhanced Text Classification through various Frequency Weighting proposes the estimation of improving accuracy through implying various weighting strategies in SVM and Maximum Entropy algorithms using Yelp review dataset.
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published