private static IEstimator <ITransformer> CreateInstance(MLContext context, string[] inColumns, string[] outColumns)
        {
            var cols = new InputOutputColumnPair[inColumns.Length];

            for (var i = 0; i < cols.Length; i++)
            {
                cols[i] = new InputOutputColumnPair(outColumns[i], inColumns[i]);
            }
            return(context.Transforms.Categorical.OneHotHashEncoding(cols));
        }
        private static IEstimator <ITransformer> CreateInstance(MLContext context, string[] inColumns, string[] outColumns)
        {
            var cols = new InputOutputColumnPair[inColumns.Length];

            for (var i = 0; i < cols.Length; i++)
            {
                cols[i] = new InputOutputColumnPair(outColumns[i], inColumns[i]);
            }
            return(context.Transforms.Conversion.ConvertType(cols));
        }
        private static IEstimator <ITransformer> CreateInstance(MLContext context, string[] inColumns, string[] outColumns)
        {
            var pairs = new InputOutputColumnPair[inColumns.Length];

            for (var i = 0; i < inColumns.Length; i++)
            {
                var pair = new InputOutputColumnPair(outColumns[i], inColumns[i]);
                pairs[i] = pair;
            }
            return(context.Transforms.IndicateMissingValues(pairs));
        }
Exemplo n.º 4
0
 /// <summary>
 /// Returns the names of the input-output column pairs on which the transformation is applied.
 /// </summary>
 public static IReadOnlyList <InputOutputColumnPair> GetColumnPairs(this OneToOneTransformerBase transformer) =>
 InputOutputColumnPair.ConvertFromValueTuples(transformer.ColumnPairs);