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I have a simple use case where RubixML can help me achieve 90% of the hardwork, put I'm missing a final result Class.
I would like to have your advice on how to best design / architect the code to keep it RubixML friendly.
RubixML already as all the necessary utility classes : Transformers\TfIdfTransformer, Kernel/Distance/Cosine and other useful tools to preprocess.
I think that what I'm missing is an Estimator Class that can output the result of the TfIdfTransformer.
I have created a new TF-IDF similarity ranking Estimator Class
class TfIdfRankerEstimator implements Estimator, Verbose, Persistable
{
use AutotrackRevisions, LoggerAware;
private $logger;
/**
* The distance kernel to use when computing the distances between samples.
*
* @var \Rubix\ML\Kernels\Distance\Distance
*/
protected \Rubix\ML\Kernels\Distance\Distance $kernel;
// Number of ranks results to return as int
protected int $numberRankedResults;
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Dear RubixML Team,
I have a simple use case where RubixML can help me achieve 90% of the hardwork, put I'm missing a final result Class.
I would like to have your advice on how to best design / architect the code to keep it RubixML friendly.
RubixML already as all the necessary utility classes : Transformers\TfIdfTransformer, Kernel/Distance/Cosine and other useful tools to preprocess.
I think that what I'm missing is an Estimator Class that can output the result of the TfIdfTransformer.
I have created a new TF-IDF similarity ranking Estimator Class
Am I on the right path ?
Regards
Guillaume
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