Fix a bug regarding to overflow

v123

fix overflow when model size > 2^31

Some minor fixes

v122

closing file f_in in ffm-predict.cpp

Windows support

v121

Windows support

Restruct

• Binary model

  In old version the model is in text file and it was very slow for saving and loading. To make it faster, we decide to use binary format.

• Removed C API support

  In the old version in order to support pure C API, the code inside LIBFFM is writing in a mixed C++ / C style. This is very buggy and ugly. We decide to stop providing C API in this version. If you need this, let us know and we will consider to write a wrapper.

• Remove cross-validation

  FFM so far has been shown useful for large scale categorical data. Because the dataset are usually large, it will take a very long time to do cross-validation. Indeed, ourselves have never used cross-validation (including when we were attending the Criteo and the Avazu contest). We think this function is a overkill so we decided to remove it.

• Remove in memory training

  We find that on-disk training has very similar performance as in memory training but consuming way smaller memory. So we decide to remove in memory training and use on-disk version only.

• Support random in on-disk mode

  In previous version the selection of data point is not randomized in on-disk mode.

• Binary data file reuse

  Converting text file to binary file is slow. In this version you only need to convert once and we will automatically reuse the binary.

• Add timer

  Now we output the training time