public void TestOldSavingAndLoading()
{
var data = new[] { new TestClass()
{
A = "1", B = "2", C = "3",
}, new TestClass()
{
A = "4", B = "5", C = "6"
} };
var dataView = ComponentCreation.CreateDataView(Env, data);
var pipe = new CategoricalHashEstimator(Env, new[] {
new CategoricalHashEstimator.ColumnInfo("A", "CatHashA"),
new CategoricalHashEstimator.ColumnInfo("B", "CatHashB"),
new CategoricalHashEstimator.ColumnInfo("C", "CatHashC")
});
var result = pipe.Fit(dataView).Transform(dataView);
var resultRoles = new RoleMappedData(result);
using (var ms = new MemoryStream())
{
TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles);
ms.Position = 0;
var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);
}
}
public void TestMetadataPropagation()
{
var data = new[] {
new TestMeta()
{
A = new string[2] {
"A", "B"
}, B = "C", C = new float[2] {
1.0f, 2.0f
}, D = 1.0f, E = new string[2] {
"A", "D"
}, F = "D"
},
new TestMeta()
{
A = new string[2] {
"A", "B"
}, B = "C", C = new float[2] {
3.0f, 4.0f
}, D = -1.0f, E = new string[2] {
"E", "A"
}, F = "E"
},
new TestMeta()
{
A = new string[2] {
"A", "B"
}, B = "C", C = new float[2] {
5.0f, 6.0f
}, D = 1.0f, E = new string[2] {
"D", "E"
}, F = "D"
}
};
var dataView = ComponentCreation.CreateDataView(Env, data);
var bagPipe = new CategoricalHashEstimator(Env,
new CategoricalHashEstimator.ColumnInfo("A", "CatA", CategoricalTransform.OutputKind.Bag, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("B", "CatB", CategoricalTransform.OutputKind.Bag, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("C", "CatC", CategoricalTransform.OutputKind.Bag, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("D", "CatD", CategoricalTransform.OutputKind.Bag, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("E", "CatE", CategoricalTransform.OutputKind.Ind, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("F", "CatF", CategoricalTransform.OutputKind.Ind, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("A", "CatG", CategoricalTransform.OutputKind.Key, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("B", "CatH", CategoricalTransform.OutputKind.Key, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("A", "CatI", CategoricalTransform.OutputKind.Bin, invertHash: -1),
new CategoricalHashEstimator.ColumnInfo("B", "CatJ", CategoricalTransform.OutputKind.Bin, invertHash: -1));
var bagResult = bagPipe.Fit(dataView).Transform(dataView);
ValidateMetadata(bagResult);
Done();
}
public void CategoricalHashWorkout()
{
var data = new[] { new TestClass()
{
A = "1", B = "2", C = "3",
}, new TestClass()
{
A = "4", B = "5", C = "6"
} };
var dataView = ComponentCreation.CreateDataView(Env, data);
var pipe = new CategoricalHashEstimator(Env, new[] {
new CategoricalHashEstimator.ColumnInfo("A", "CatA", CategoricalTransform.OutputKind.Bag),
new CategoricalHashEstimator.ColumnInfo("A", "CatB", CategoricalTransform.OutputKind.Bin),
new CategoricalHashEstimator.ColumnInfo("A", "CatC", CategoricalTransform.OutputKind.Ind),
new CategoricalHashEstimator.ColumnInfo("A", "CatD", CategoricalTransform.OutputKind.Key),
});
TestEstimatorCore(pipe, dataView);
Done();
}
