4 writes to NumberOfIterations
Microsoft.ML.Samples (2)
Dynamic\Trainers\BinaryClassification\SgdCalibratedWithOptions.cs (1)
33
NumberOfIterations
= 30,
Dynamic\Trainers\BinaryClassification\SgdNonCalibratedWithOptions.cs (1)
31
NumberOfIterations
= 10,
Microsoft.ML.StandardTrainers (1)
Standard\SdcaBinary.cs (1)
1980
_options.
NumberOfIterations
= maxIterations;
Microsoft.ML.Tests (1)
TrainerEstimators\TrainerEstimators.cs (1)
93
ML.BinaryClassification.Trainers.SgdCalibrated(new Trainers.SgdCalibratedTrainer.Options(){ L2Regularization = 0,
NumberOfIterations
= 80})};
10 references to NumberOfIterations
Microsoft.ML.StandardTrainers (10)
Standard\SdcaBinary.cs (10)
1920
env.CheckUserArg(
NumberOfIterations
> 0, nameof(
NumberOfIterations
), "Must be positive.");
2072
if (e % checkFrequency == 0 && e != _options.
NumberOfIterations
)
2098
pch.Checkpoint(loss, improvement, e, _options.
NumberOfIterations
);
2108
var trainingTasks = new Action<Random, IProgressChannel>[_options.
NumberOfIterations
];
2109
var rands = new Random[_options.
NumberOfIterations
];
2112
for (int epoch = 1; epoch <= _options.
NumberOfIterations
; epoch++)
2173
entry => entry.SetProgress(0, iter, _options.
NumberOfIterations
));
2175
for (int i = 0; i < _options.
NumberOfIterations
; i++)
2193
Parallel.For(0, _options.
NumberOfIterations
, pOptions, i => trainingTasks[i](rands[i], pch));