public void GaussDeNormalizationTestsn_test1()
{
// Creates learning api object
LearningApi api = new LearningApi(loadMetaData1());
//Real dataset must be defined as object type, because data can be numeric, binary and classification
api.UseActionModule <object[][], object[][]>((input, ctx) =>
{
return(GetRealDataSample());
});
//this call must be first in the pipeline
api.UseDefaultDataMapper();
//
api.UseGaussNormalizer();
//use denormalizer on normalized data
api.UseGaussDeNormalizer();
//
var result = api.Run() as double[][];
//Test result for normalization
var expected = GetTransformedNumericDataSample();
for (int i = 0; i < expected.Length; i++)
{
for (int j = 0; j < expected[0].Length; j++)
{
Assert.Equal(Math.Round(result[i][j], 4), expected[i][j]);
}
}
//
return;
}
