45 instantiations of SweepableDiscreteParam
Microsoft.ML.AutoML (45)
TrainerExtensions\SweepableParams.cs (44)
17
new
SweepableDiscreteParam
("LearningRate", new object[] { 0.01f, 0.1f, 0.5f, 1.0f}),
18
new
SweepableDiscreteParam
("DecreaseLearningRate", new object[] { false, true }),
29
new
SweepableDiscreteParam
("Shuffle", new object[] { false, true }),
38
new
SweepableDiscreteParam
("MinimumExampleCountPerLeaf", new object[] { 1, 10, 50 }),
39
new
SweepableDiscreteParam
("NumberOfTrees", new object[] { 20, 100, 500 }),
57
new
SweepableDiscreteParam
("OptimizationTolerance", new object[] { 1e-4f, 1e-7f }),
58
new
SweepableDiscreteParam
("HistorySize", new object[] { 5, 20, 50 }),
61
new
SweepableDiscreteParam
("DenseOptimizer", new object[] { false, true }),
94
new
SweepableDiscreteParam
("UseSoftmax", new object[] { true, false }),
102
new
SweepableDiscreteParam
("NumberOfIterations", new object[] { 10, 20, 50, 100, 150, 200 }),
105
new
SweepableDiscreteParam
("MinimumExampleCountPerLeaf", new object[] { 1, 10, 20, 50 }),
106
new
SweepableDiscreteParam
("UseCategoricalSplit", new object[] { true, false }),
107
new
SweepableDiscreteParam
("HandleMissingValue", new object[] { true, false }),
108
new
SweepableDiscreteParam
("UseZeroAsMissingValue", new object[] { true, false }),
109
new
SweepableDiscreteParam
("MinimumExampleCountPerGroup", new object[] { 10, 50, 100, 200 }),
110
new
SweepableDiscreteParam
("MaximumCategoricalSplitPointCount", new object[] { 8, 16, 32, 64 }),
111
new
SweepableDiscreteParam
("CategoricalSmoothing", new object[] { 1, 10, 20 }),
112
new
SweepableDiscreteParam
("L2CategoricalRegularization", new object[] { 0.1, 0.5, 1, 5, 10 }),
115
new
SweepableDiscreteParam
("L2Regularization", new object[] { 0f, 0.5f, 1f }),
116
new
SweepableDiscreteParam
("L1Regularization", new object[] { 0f, 0.5f, 1f })
124
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.NumberOfIterations), new object[] { 10, 20, 40 }),
125
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.LearningRate), new object[] { 0.001f, 0.01f, 0.1f }),
126
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.ApproximationRank), new object[] { 8, 16, 64, 128 }),
127
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.Lambda), new object[] { 0.01f, 0.05f, 0.1f, 0.5f, 1f }),
128
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.LossFunction), new object[] { MatrixFactorizationTrainer.LossFunctionType.SquareLossRegression, MatrixFactorizationTrainer.LossFunctionType.SquareLossOneClass }),
129
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.Alpha), new object[] { 1f, 0.01f, 0.0001f, 0.000001f }),
130
new
SweepableDiscreteParam
(nameof(MatrixFactorizationTrainer.Options.C), new object[] { 0.000001f, 0.0001f, 0.01f }),
137
new
SweepableDiscreteParam
("PerformProjection", null, isBool: true),
138
new
SweepableDiscreteParam
("NoBias", null, isBool: true)
160
new
SweepableDiscreteParam
("L2Regularization", new object[] { "<Auto>", 1e-7f, 1e-6f, 1e-5f, 1e-4f, 1e-3f, 1e-2f }),
161
new
SweepableDiscreteParam
("L1Regularization", new object[] { "<Auto>", 0f, 0.25f, 0.5f, 0.75f, 1f }),
162
new
SweepableDiscreteParam
("ConvergenceTolerance", new object[] { 0.001f, 0.01f, 0.1f, 0.2f }),
163
new
SweepableDiscreteParam
("MaximumNumberOfIterations", new object[] { "<Auto>", 10, 20, 100 }),
164
new
SweepableDiscreteParam
("Shuffle", null, isBool: true),
165
new
SweepableDiscreteParam
("BiasLearningRate", new object[] { 0.0f, 0.01f, 0.1f, 1f })
172
new
SweepableDiscreteParam
("L2Regularization", new object[] { 1e-6f, 0.1f, 1f })
179
new
SweepableDiscreteParam
("L2Regularization", new object[] { 1e-7f, 5e-7f, 1e-6f, 5e-6f, 1e-5f }),
180
new
SweepableDiscreteParam
("ConvergenceTolerance", new object[] { 1e-2f, 1e-3f, 1e-4f, 1e-5f }),
181
new
SweepableDiscreteParam
("NumberOfIterations", new object[] { 1, 5, 10, 20 }),
182
new
SweepableDiscreteParam
("Shuffle", null, isBool: true),
189
new
SweepableDiscreteParam
("NumberOfIterations", new object[] { 1, 5, 10, 20, 30, 40, 50 }),
190
new
SweepableDiscreteParam
("LearningRate", new object[] { "<Auto>", 1e1f, 1e0f, 1e-1f, 1e-2f, 1e-3f }),
191
new
SweepableDiscreteParam
("L2Regularization", new object[] { 0.0f, 1e-5f, 1e-5f, 1e-6f, 1e-7f }),
192
new
SweepableDiscreteParam
("UpdateFrequency", new object[] { "<Auto>", 5, 20 })
Utils\SweepableParamAttributes.cs (1)
110
new
SweepableDiscreteParam
(Name, Options) { RawValue = RawValue, Frozen = Frozen };
2 references to SweepableDiscreteParam
Microsoft.ML.AutoML (2)
PipelineSuggesters\PipelineSuggester.cs (1)
139
case
SweepableDiscreteParam
dp:
TrainerExtensions\TrainerExtensionUtil.cs (1)
267
if (param is
SweepableDiscreteParam
dp)