params.py

# [name, epoch, iter, batch_size, [No. of training sample, No. of validation sample, No. of test sample, No. of features, No. of nonzero features]]
criteo = ['criteo', 400, 100, 16384, [36673655, 4581990, 4584972, 1086901, 39], 'log_loss']
frappe_l = ['frappe_l', 200, 1000, 256, [202027, 57722, 28860, 5382, 10], 'log_loss']
# criteo_s = ['criteo_s', 200, 100, 16384, [3667365, 458199, 458497, 1086901, 39], 32, 'log_loss']
ml_tag_l = ['ml-tag_l', 200, 100, 4096, [1404801, 401372, 200686, 90445, 3], 'log_loss']
avazu = ['avazu', 400, 100, 16384, [32344895, 4042704, 4041368, 570344, 21], 'log_loss']
amusic = ['amusic', 200, 500, 256, [52395, 6414, 6535, 14996, 2], 'square_loss']
amovie = ['amovie', 400, 500, 256, [963660, 120925, 120103, 98340, 2], 'square_loss']
ml_1m = ['ml-1m', 400, 500, 4096, [800000, 99685, 100524, 9746, 2], 'square_loss']
ml_10m = ['ml-10m', 200, 500, 16384, [7999752, 1000564, 999738, 80555, 2], 'square_loss']
ml_20m = ['ml-20m', 200, 500, 16384, [15998245, 2002102, 1999916, 165237, 2], 'square_loss']