I am using LibSVM (3.18) as an implementation of SVM. But every time when I'm predicting the result, it's giving zero.
I am following these instructions:
- I have CSV file (+50K lines), Most of data in column (target) is zeros, the other values are between 1-10.
- I convert csv file to libsvm data by selecting this column as label.
When I Scale Data, I use these parameters
$ svm-scale -l 0 -u 1 data.cv>scaled.data
As I have a huge file, I use Subset.py.
When I finish all the steps and apply predict. I got good result of accuracy.
$svm-predict scaled_data.csv model.train data.predicted
Accuracy = 94.28%
but the file I get (data.predicted) contains only zeros.
What does this mean statistically ?
Is it tricky to predict this kind of data ? Is there any way to solve this problem ?