Description Usage Arguments Details
Auxiliary functions for optimization routines
1 | solver.control(max_iter = 10000, convergence = 1e-4, evaluate.metric = "LL", solver = TDAP.solver())
|
max_iter |
integer giving maximal number of iterations, 25 for MCMC/ALS and 10000 for other optimization routines by default |
solver |
function to set parameters of optimization routine |
SGD/FTRL/TDAP updates model every single example, while MCMC/ALS needs to sweeps through all the data for each update. So the maximal number of iterations of MCMC/ALS is much smaller, which is 25 by default.
By now, only MCMC and ALS support parallel computing.
solver is a function to set parameters of optimization routine further, including ALS.solver MCMC.solver SGD.solver TDAP.solver FTRL.solver
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