/// <summary>
/// Infers information about the columns of a dataset in a file located at <paramref name="path"/>.
/// </summary>
/// <param name="path">Path to a dataset file.</param>
/// <param name="columnInformation">Column information for the dataset.</param>
/// <param name="separatorChar">The character used as separator between data elements in a row. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="allowQuoting">Whether the file can contain columns defined by a quoted string. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="allowSparse">Whether the file can contain numerical vectors in sparse format. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="trimWhitespace">Whether trailing whitespace should be removed from dataset file lines.</param>
/// <param name="groupColumns">Whether to group together (when possible) original columns in the dataset file into vector columns in the resulting data structures. See <see cref="TextLoader.Range"/> for more information.</param>
/// <returns>Information inferred about the columns in the provided dataset.</returns>
/// <remarks>
/// Infers information about the name, data type, and purpose of each column.
/// The returned <see cref="ColumnInferenceResults.TextLoaderOptions" /> can be used to
/// instantiate a <see cref="TextLoader" />. The <see cref="TextLoader" /> can be used to
/// obtain an <see cref="IDataView"/> that can be fed into an AutoML experiment,
/// or used elsewhere in the ML.NET ecosystem (ie in <see cref="IEstimator{TTransformer}.Fit(IDataView)"/>.
/// The <see cref="ColumnInformation"/> contains the inferred purpose of each column in the dataset.
/// (For instance, is the column categorical, numeric, or text data? Should the column be ignored? Etc.)
/// The <see cref="ColumnInformation"/> can be inspected and modified (or kept as is) and used by an AutoML experiment.
/// </remarks>
public ColumnInferenceResults InferColumns(string path, ColumnInformation columnInformation, char?separatorChar = null, bool?allowQuoting = null,
bool?allowSparse = null, bool trimWhitespace = false, bool groupColumns = true)
{
columnInformation = columnInformation ?? new ColumnInformation();
UserInputValidationUtil.ValidateInferColumnsArgs(path, columnInformation);
return(ColumnInferenceApi.InferColumns(_context, path, columnInformation, separatorChar, allowQuoting, allowSparse, trimWhitespace, groupColumns));
}
/// <summary>
/// Infers information about the columns of a dataset in a file located at <paramref name="path"/>.
/// </summary>
/// <param name="path">Path to a dataset file.</param>
/// <param name="labelColumnIndex">Column index of the label column in the dataset.</param>
/// <param name="hasHeader">Whether or not the dataset file has a header row.</param>
/// <param name="separatorChar">The character used as separator between data elements in a row. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="allowQuoting">Whether the file can contain columns defined by a quoted string. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="allowSparse">Whether the file can contain numerical vectors in sparse format. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="trimWhitespace">Whether trailing whitespace should be removed from dataset file lines.</param>
/// <param name="groupColumns">Whether to group together (when possible) original columns in the dataset file into vector columns in the resulting data structures. See <see cref="TextLoader.Range"/> for more information.</param>
/// <returns>Information inferred about the columns in the provided dataset.</returns>
/// <remarks>
/// Infers information about the name, data type, and purpose of each column.
/// The returned <see cref="ColumnInferenceResults.TextLoaderOptions" /> can be used to
/// instantiate a <see cref="TextLoader" />. The <see cref="TextLoader" /> can be used to
/// obtain an <see cref="IDataView"/> that can be fed into an AutoML experiment,
/// or used elsewhere in the ML.NET ecosystem (ie in <see cref="IEstimator{TTransformer}.Fit(IDataView)"/>.
/// The <see cref="ColumnInformation"/> contains the inferred purpose of each column in the dataset.
/// (For instance, is the column categorical, numeric, or text data? Should the column be ignored? Etc.)
/// The <see cref="ColumnInformation"/> can be inspected and modified (or kept as is) and used by an AutoML experiment.
/// </remarks>
public ColumnInferenceResults InferColumns(string path, uint labelColumnIndex, bool hasHeader = false, char?separatorChar = null,
bool?allowQuoting = null, bool?allowSparse = null, bool trimWhitespace = false, bool groupColumns = true)
{
UserInputValidationUtil.ValidateInferColumnsArgs(path);
return(ColumnInferenceApi.InferColumns(_context, path, labelColumnIndex, hasHeader, separatorChar, allowQuoting, allowSparse, trimWhitespace, groupColumns));
}
/// <summary>
/// Infers information about the columns of a dataset in a file located at <paramref name="path"/>.
/// </summary>
/// <param name="path">Path to a dataset file.</param>
/// <param name="labelColumnName">The name of the label column.</param>
/// <param name="separatorChar">The character used as separator between data elements in a row. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="allowQuoting">Whether the file can contain columns defined by a quoted string. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="allowSparse">Whether the file can contain numerical vectors in sparse format. If <see langword="null"/>, AutoML will try to infer this value.</param>
/// <param name="trimWhitespace">Whether trailing whitespace should be removed from dataset file lines.</param>
/// <param name="groupColumns">Whether to group together (when possible) original columns in the dataset file into vector columns in the resulting data structures. See <see cref="TextLoader.Range"/> for more information.</param>
/// <returns>Information inferred about the columns in the provided dataset.</returns>
/// <remarks>
/// Infers information about the name, data type, and purpose of each column.
/// The returned <see cref="ColumnInferenceResults.TextLoaderOptions" /> can be used to
/// instantiate a <see cref="TextLoader" />. The <see cref="TextLoader" /> can be used to
/// obtain an <see cref="IDataView"/> that can be fed into an AutoML experiment,
/// or used elsewhere in the ML.NET ecosystem (ie in <see cref="IEstimator{TTransformer}.Fit(IDataView)"/>.
/// The <see cref="ColumnInformation"/> contains the inferred purpose of each column in the dataset.
/// (For instance, is the column categorical, numeric, or text data? Should the column be ignored? Etc.)
/// The <see cref="ColumnInformation"/> can be inspected and modified (or kept as is) and used by an AutoML experiment.
/// </remarks>
public ColumnInferenceResults InferColumns(string path, string labelColumnName = DefaultColumnNames.Label, char?separatorChar = null, bool?allowQuoting = null,
bool?allowSparse = null, bool trimWhitespace = false, bool groupColumns = true)
{
UserInputValidationUtil.ValidateInferColumnsArgs(path, labelColumnName);
return(ColumnInferenceApi.InferColumns(_context, path, labelColumnName, separatorChar, allowQuoting, allowSparse, trimWhitespace, groupColumns));
}