I have this data set that is word counts for top 5k words, 5000 observations training, 5000 hold out. I consider this data pretty small.
SVM with rbf kernal can get around 87-88% accuracy, but a histogram kernal can get around 89.7% accuracy with a little feature engineering.
Tensorflow, after tuning some parameters, can also get around 89.7% accuracy as well.
I have this data set that is word counts for top 5k words, 5000 observations training, 5000 hold out. I consider this data pretty small.
SVM with rbf kernal can get around 87-88% accuracy, but a histogram kernal can get around 89.7% accuracy with a little feature engineering.
Tensorflow, after tuning some parameters, can also get around 89.7% accuracy as well.