- Machine learning with large data samples
- 29 Oct 2017 02:56:41 pm Permalink
Hello everyone I'm looking to perform a binary classification (either 0 or 1) on a large sample of data (around 5 million points). The data is numerical; i.e. [1,4,6,2,3,0,3,...], and I would like to be able to train a model to accept multiple samples of pre-classified data; which would then be able to generate a prediction on an entirely new set of data. I've been looking into SVM types of learning; however it seems this may not be exactly what I want. Any suggestions or advice would be much appreciated! I'd be happy to answer any questions you may have.