This is the last stretch for the analysis, we need to take the large feature set we are generating and train. The SVM might be a problem here, so we need to do a test run to check if it can handle the amount of data we will be feeding it. The code for the classification is simple enough as it was already developed in the other tasks, however the main problem will be to install the dependencies properly as I didnt use a virtualenv while working on this project (used conda instead). I just learned that conda is not supported in the cluster so I have to install the stuff with pip. Good news is that scipy is already pre-installed properly, I just need to make sure that I install sklearn correctly.
This is the last stretch for the analysis, we need to take the large feature set we are generating and train. The SVM might be a problem here, so we need to do a test run to check if it can handle the amount of data we will be feeding it. The code for the classification is simple enough as it was already developed in the other tasks, however the main problem will be to install the dependencies properly as I didnt use a virtualenv while working on this project (used conda instead). I just learned that conda is not supported in the cluster so I have to install the stuff with pip. Good news is that scipy is already pre-installed properly, I just need to make sure that I install sklearn correctly.