diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs
index 78c62668ec..8084c31413 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/Calibrator.cs
@@ -28,7 +28,7 @@ public static void Calibration()
var mlContext = new MLContext();
// Create a text loader.
- var reader = mlContext.Data.CreateTextReader(new TextLoader.Arguments()
+ var reader = mlContext.Data.CreateTextLoader(new TextLoader.Arguments()
{
Separator = "tab",
HasHeader = true,
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs
index 3af22fba9b..e100a0fea7 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureContributionCalculationTransform.cs
@@ -18,7 +18,7 @@ public static void FeatureContributionCalculationTransform_Regression()
// Step 1: Read the data as an IDataView.
// First, we define the reader: specify the data columns and where to find them in the text file.
- var reader = mlContext.Data.CreateTextReader(
+ var reader = mlContext.Data.CreateTextLoader(
columns: new[]
{
new TextLoader.Column("MedianHomeValue", DataKind.R4, 0),
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs
index aa3d4446bb..fdeaf6f42c 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FeatureSelectionTransform.cs
@@ -30,7 +30,7 @@ public static void FeatureSelectionTransform()
// First, we define the reader: specify the data columns and where to find them in the text file. Notice that we combine entries from
// all the feature columns into entries of a vector of a single column named "Features".
- var reader = ml.Data.CreateTextReader(
+ var reader = ml.Data.CreateTextLoader(
columns: new[]
{
new TextLoader.Column("Label", DataKind.BL, 0),
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs
index 812de0fd27..9c8d9d6039 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/FieldAwareFactorizationMachine.cs
@@ -22,7 +22,7 @@ public static void FFM_BinaryClassification()
// Step 1: Read the data as an IDataView.
// First, we define the reader: specify the data columns and where to find them in the text file.
- var reader = mlContext.Data.CreateTextReader(
+ var reader = mlContext.Data.CreateTextLoader(
columns: new[]
{
new TextLoader.Column("Sentiment", DataKind.BL, 0),
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs
index acd08979a2..9b27c88d5c 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/GeneralizedAdditiveModels.cs
@@ -19,7 +19,7 @@ public static void RunExample()
// Step 1: Read the data as an IDataView.
// First, we define the reader: specify the data columns and where to find them in the text file.
- var reader = mlContext.Data.CreateTextReader(
+ var reader = mlContext.Data.CreateTextLoader(
columns: new[]
{
new TextLoader.Column("MedianHomeValue", DataKind.R4, 0),
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs
index ebb4def616..f8f1fab34e 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/PermutationFeatureImportance/PFIHelper.cs
@@ -19,7 +19,7 @@ public static IDataView GetHousingRegressionIDataView(MLContext mlContext, out s
// First, we define the reader: specify the data columns and where to find them in the text file.
// The data file is composed of rows of data, with each row having 11 numerical columns
// separated by whitespace.
- var reader = mlContext.Data.CreateTextReader(
+ var reader = mlContext.Data.CreateTextLoader(
columns: new[]
{
// Read the first column (indexed by 0) in the data file as an R4 (float)
diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs
index 5f08dee906..1d2b04280c 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/SDCA.cs
@@ -24,7 +24,7 @@ public static void SDCA_BinaryClassification()
// Step 1: Read the data as an IDataView.
// First, we define the reader: specify the data columns and where to find them in the text file.
- var reader = mlContext.Data.CreateTextReader(
+ var reader = mlContext.Data.CreateTextLoader(
columns: new[]
{
new TextLoader.Column("Sentiment", DataKind.BL, 0),
diff --git a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs
index 882c6d5998..05800fdec8 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Text/TextLoaderSaverCatalog.cs
@@ -11,14 +11,14 @@ namespace Microsoft.ML
public static class TextLoaderSaverCatalog
{
///
- /// Create a text reader .
+ /// Create a text loader .
///
/// The catalog.
- /// The columns of the schema.
+ /// Array of columns defining the schema.
/// Whether the file has a header.
/// The character used as separator between data points in a row. By default the tab character is used as separator.
- /// The optional location of a data sample.
- public static TextLoader CreateTextReader(this DataOperations catalog,
+ /// The optional location of a data sample. The sample can be used to infer column names and number of slots in each column.
+ public static TextLoader CreateTextLoader(this DataOperations catalog,
TextLoader.Column[] columns,
bool hasHeader = TextLoader.DefaultArguments.HasHeader,
char separatorChar = TextLoader.DefaultArguments.Separator,
@@ -26,18 +26,18 @@ public static TextLoader CreateTextReader(this DataOperations catalog,
=> new TextLoader(CatalogUtils.GetEnvironment(catalog), columns, hasHeader, separatorChar, dataSample);
///
- /// Create a text reader .
+ /// Create a text loader .
///
/// The catalog.
/// Defines the settings of the load operation.
- /// Allows to expose items that can be used for reading.
- public static TextLoader CreateTextReader(this DataOperations catalog,
+ /// The optional location of a data sample. The sample can be used to infer column names and number of slots in each column.
+ public static TextLoader CreateTextLoader(this DataOperations catalog,
TextLoader.Arguments args,
IMultiStreamSource dataSample = null)
=> new TextLoader(CatalogUtils.GetEnvironment(catalog), args, dataSample);
///
- /// Create a text reader by inferencing the dataset schema from a data model type.
+ /// Create a text loader by inferencing the dataset schema from a data model type.
///
/// The catalog.
/// Does the file contains header?
@@ -51,7 +51,7 @@ public static TextLoader CreateTextReader(this DataOperations catalog,
/// if one of the row contains "5 2:6 4:3" that's mean there are 5 columns all zero
/// except for 3rd and 5th columns which have values 6 and 3
/// Remove trailing whitespace from lines
- public static TextLoader CreateTextReader(this DataOperations catalog,
+ public static TextLoader CreateTextLoader(this DataOperations catalog,
bool hasHeader = TextLoader.DefaultArguments.HasHeader,
char separatorChar = TextLoader.DefaultArguments.Separator,
bool allowQuotedStrings = TextLoader.DefaultArguments.AllowQuoting,
diff --git a/test/Microsoft.ML.Benchmarks/RffTransform.cs b/test/Microsoft.ML.Benchmarks/RffTransform.cs
index 1b486a1551..7ca9c76c83 100644
--- a/test/Microsoft.ML.Benchmarks/RffTransform.cs
+++ b/test/Microsoft.ML.Benchmarks/RffTransform.cs
@@ -27,7 +27,7 @@ public void SetupTrainingSpeedTests()
public void CV_Multiclass_Digits_RffTransform_OVAAveragedPerceptron()
{
var mlContext = new MLContext();
- var reader = mlContext.Data.CreateTextReader(new TextLoader.Arguments
+ var reader = mlContext.Data.CreateTextLoader(new TextLoader.Arguments
{
Column = new[]
{
diff --git a/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs b/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs
index edb6bd5e86..eab8280104 100644
--- a/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs
+++ b/test/Microsoft.ML.Predictor.Tests/TestIniModels.cs
@@ -521,7 +521,7 @@ public TestIniModels(ITestOutputHelper output) : base(output)
public void TestGamRegressionIni()
{
var mlContext = new MLContext(seed: 0);
- var idv = mlContext.Data.CreateTextReader(
+ var idv = mlContext.Data.CreateTextLoader(
new TextLoader.Arguments()
{
HasHeader = false,
@@ -560,7 +560,7 @@ public void TestGamRegressionIni()
public void TestGamBinaryClassificationIni()
{
var mlContext = new MLContext(seed: 0);
- var idv = mlContext.Data.CreateTextReader(
+ var idv = mlContext.Data.CreateTextLoader(
new TextLoader.Arguments()
{
HasHeader = false,
diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs
index 2d00f36957..2e1ff30ad8 100644
--- a/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/Api/CookbookSamples/CookbookSamplesDynamicApi.cs
@@ -249,7 +249,7 @@ private void TextFeaturizationOn(string dataPath)
var mlContext = new MLContext();
// Define the reader: specify the data columns and where to find them in the text file.
- var reader = mlContext.Data.CreateTextReader(new[]
+ var reader = mlContext.Data.CreateTextLoader(new[]
{
new TextLoader.Column("IsToxic", DataKind.BL, 0),
new TextLoader.Column("Message", DataKind.TX, 1),
@@ -316,7 +316,7 @@ private void CategoricalFeaturizationOn(params string[] dataPath)
var mlContext = new MLContext();
// Define the reader: specify the data columns and where to find them in the text file.
- var reader = mlContext.Data.CreateTextReader(new[]
+ var reader = mlContext.Data.CreateTextLoader(new[]
{
new TextLoader.Column("Label", DataKind.BL, 0),
// We will load all the categorical features into one vector column of size 8.
diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs
index 5d890cf7b8..142e2f96ad 100644
--- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Evaluation.cs
@@ -22,7 +22,7 @@ public void Evaluation()
var ml = new MLContext(seed: 1, conc: 1);
// Pipeline.
- var pipeline = ml.Data.CreateTextReader(TestDatasets.Sentiment.GetLoaderColumns(), hasHeader: true)
+ var pipeline = ml.Data.CreateTextLoader(TestDatasets.Sentiment.GetLoaderColumns(), hasHeader: true)
.Append(ml.Transforms.Text.FeaturizeText("SentimentText", "Features"))
.Append(ml.BinaryClassification.Trainers.StochasticDualCoordinateAscent("Label", "Features", advancedSettings: s => s.NumThreads = 1));
diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs
index 84bd6691e9..71d05f175f 100644
--- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Extensibility.cs
@@ -26,7 +26,7 @@ void Extensibility()
var dataPath = GetDataPath(TestDatasets.irisData.trainFilename);
var ml = new MLContext();
- var data = ml.Data.CreateTextReader(TestDatasets.irisData.GetLoaderColumns(), separatorChar: ',')
+ var data = ml.Data.CreateTextLoader(TestDatasets.irisData.GetLoaderColumns(), separatorChar: ',')
.Read(dataPath);
Action action = (i, j) =>
diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs
index afae98455c..b9108239da 100644
--- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/FileBasedSavingOfData.cs
@@ -25,7 +25,7 @@ void FileBasedSavingOfData()
var ml = new MLContext(seed: 1, conc: 1);
var src = new MultiFileSource(GetDataPath(TestDatasets.Sentiment.trainFilename));
- var trainData = ml.Data.CreateTextReader(TestDatasets.Sentiment.GetLoaderColumns(), hasHeader: true)
+ var trainData = ml.Data.CreateTextLoader(TestDatasets.Sentiment.GetLoaderColumns(), hasHeader: true)
.Append(ml.Transforms.Text.FeaturizeText("SentimentText", "Features"))
.Fit(src).Read(src);
diff --git a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs
index 2ef382e5d5..4d39f774c8 100644
--- a/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/Api/Estimators/Visibility.cs
@@ -23,7 +23,7 @@ public partial class ApiScenariosTests
void Visibility()
{
var ml = new MLContext(seed: 1, conc: 1);
- var pipeline = ml.Data.CreateTextReader(TestDatasets.Sentiment.GetLoaderColumns(), hasHeader: true)
+ var pipeline = ml.Data.CreateTextLoader(TestDatasets.Sentiment.GetLoaderColumns(), hasHeader: true)
.Append(ml.Transforms.Text.FeaturizeText("SentimentText", "Features", s => s.OutputTokens = true));
var src = new MultiFileSource(GetDataPath(TestDatasets.Sentiment.trainFilename));
diff --git a/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs b/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs
index f3906ca806..1056cdf16e 100644
--- a/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationTests.cs
@@ -17,7 +17,7 @@ public void TrainAndPredictIrisModelTest()
{
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(columns: new[]
+ var reader = mlContext.Data.CreateTextLoader(columns: new[]
{
new TextLoader.Column("Label", DataKind.R4, 0),
new TextLoader.Column("SepalLength", DataKind.R4, 1),
diff --git a/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationWithStringLabelTests.cs b/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationWithStringLabelTests.cs
index ff38fbebe5..43fca7f4df 100644
--- a/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationWithStringLabelTests.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/IrisPlantClassificationWithStringLabelTests.cs
@@ -14,7 +14,7 @@ public void TrainAndPredictIrisModelWithStringLabelTest()
{
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(columns: new[]
+ var reader = mlContext.Data.CreateTextLoader(columns: new[]
{
new TextLoader.Column("SepalLength", DataKind.R4, 0),
new TextLoader.Column("SepalWidth", DataKind.R4, 1),
diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs
index 646eb7b148..4b4326bc12 100644
--- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs
+++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/IrisPlantClassificationTests.cs
@@ -15,7 +15,7 @@ public void TrainAndPredictIrisModelUsingDirectInstantiationTest()
{
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(columns: new[]
+ var reader = mlContext.Data.CreateTextLoader(columns: new[]
{
new TextLoader.Column("Label", DataKind.R4, 0),
new TextLoader.Column("SepalLength", DataKind.R4, 1),
diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
index 4699131680..33b3b5beb6 100644
--- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
+++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/TensorflowTests.cs
@@ -219,7 +219,7 @@ public void TensorFlowInputsOutputsSchemaTest()
public void TensorFlowTransformMNISTConvTest()
{
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(
+ var reader = mlContext.Data.CreateTextLoader(
columns: new[]
{
new TextLoader.Column("Label", DataKind.U4 , new [] { new TextLoader.Range(0) }, new KeyRange(0, 9)),
@@ -262,7 +262,7 @@ public void TensorFlowTransformMNISTLRTrainingTest()
try
{
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(columns: new[]
+ var reader = mlContext.Data.CreateTextLoader(columns: new[]
{
new TextLoader.Column("Label", DataKind.I8, 0),
new TextLoader.Column("Placeholder", DataKind.R4, new []{ new TextLoader.Range(1, 784) })
@@ -352,7 +352,7 @@ private void ExecuteTFTransformMNISTConvTrainingTest(bool shuffle, int? shuffleS
{
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(new[]
+ var reader = mlContext.Data.CreateTextLoader(new[]
{
new TextLoader.Column("Label", DataKind.U4, new []{ new TextLoader.Range(0) }, new KeyRange(0, 9)),
new TextLoader.Column("TfLabel", DataKind.I8, 0),
@@ -441,7 +441,7 @@ public void TensorFlowTransformMNISTConvSavedModelTest()
// of predicted label of a single in-memory example.
var mlContext = new MLContext(seed: 1, conc: 1);
- var reader = mlContext.Data.CreateTextReader(columns: new[]
+ var reader = mlContext.Data.CreateTextLoader(columns: new[]
{
new TextLoader.Column("Label", DataKind.U4 , new [] { new TextLoader.Range(0) }, new KeyRange(0, 9)),
new TextLoader.Column("Placeholder", DataKind.R4, new []{ new TextLoader.Range(1, 784) })
diff --git a/test/Microsoft.ML.Tests/TextLoaderTests.cs b/test/Microsoft.ML.Tests/TextLoaderTests.cs
index cffc70a22e..5c6b5841de 100644
--- a/test/Microsoft.ML.Tests/TextLoaderTests.cs
+++ b/test/Microsoft.ML.Tests/TextLoaderTests.cs
@@ -720,7 +720,7 @@ public void LoaderColumnsFromIrisData()
var irisFirstRowValues = irisFirstRow.Values.GetEnumerator();
// Simple load
- var dataIris = mlContext.Data.CreateTextReader(separatorChar: ',').Read(dataPath);
+ var dataIris = mlContext.Data.CreateTextLoader(separatorChar: ',').Read(dataPath);
var previewIris = dataIris.Preview(1);
Assert.Equal(5, previewIris.ColumnView.Length);
@@ -736,7 +736,7 @@ public void LoaderColumnsFromIrisData()
Assert.Equal("Iris-setosa", previewIris.RowView[0].Values[index].Value.ToString());
// Load with start and end indexes
- var dataIrisStartEnd = mlContext.Data.CreateTextReader(separatorChar: ',').Read(dataPath);
+ var dataIrisStartEnd = mlContext.Data.CreateTextLoader(separatorChar: ',').Read(dataPath);
var previewIrisStartEnd = dataIrisStartEnd.Preview(1);
Assert.Equal(2, previewIrisStartEnd.ColumnView.Length);
@@ -753,7 +753,7 @@ public void LoaderColumnsFromIrisData()
}
// load setting the distinct columns. Loading column 0 and 2
- var dataIrisColumnIndices = mlContext.Data.CreateTextReader(separatorChar: ',').Read(dataPath);
+ var dataIrisColumnIndices = mlContext.Data.CreateTextLoader(separatorChar: ',').Read(dataPath);
var previewIrisColumnIndices = dataIrisColumnIndices.Preview(1);
Assert.Equal(2, previewIrisColumnIndices.ColumnView.Length);
diff --git a/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs b/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs
index 0688a09aea..8c67a109a0 100644
--- a/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs
+++ b/test/Microsoft.ML.Tests/Transformers/CustomMappingTests.cs
@@ -51,7 +51,7 @@ public void TestCustomTransformer()
{
string dataPath = GetDataPath("adult.tiny.with-schema.txt");
var source = new MultiFileSource(dataPath);
- var loader = ML.Data.CreateTextReader(new[] {
+ var loader = ML.Data.CreateTextLoader(new[] {
new TextLoader.Column("Float1", DataKind.R4, 9),
new TextLoader.Column("Float4", DataKind.R4, new[]{new TextLoader.Range(9), new TextLoader.Range(10), new TextLoader.Range(11), new TextLoader.Range(12) })
}, hasHeader: true);
@@ -90,7 +90,7 @@ public void TestSchemaPropagation()
{
string dataPath = GetDataPath("adult.test");
var source = new MultiFileSource(dataPath);
- var loader = ML.Data.CreateTextReader(new[] {
+ var loader = ML.Data.CreateTextLoader(new[] {
new TextLoader.Column("Float1", DataKind.R4, 0),
new TextLoader.Column("Float4", DataKind.R4, new[]{new TextLoader.Range(0), new TextLoader.Range(2), new TextLoader.Range(4), new TextLoader.Range(10) }),
new TextLoader.Column("Text1", DataKind.Text, 0)