ITrivialEstimator (Approach 1) #2
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glebuk
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Mar 25, 2019
| /// there is no easy way to infer it from the transformer. | ||
| /// </summary> | ||
| public abstract class TrivialEstimator<TTransformer> : IEstimator<TTransformer> | ||
| public abstract class TrivialEstimator<TTransformer> : ITrivialEstimator<TTransformer> |
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TrivialEstimator [](start = 26, length = 16)
TrivialEstimatorBase
glebuk
reviewed
Mar 25, 2019
| private protected readonly IHost Host; | ||
| [BestFriend] | ||
| private protected readonly TTransformer Transformer; | ||
| internal readonly TTransformer Transformer; |
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nternal readonly TTransformer Transformer; [](start = 9, length = 42)
private protected
glebuk
reviewed
Mar 25, 2019
| } | ||
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| public TTransformer Fit(IDataView input) | ||
| public virtual TTransformer Fit(IDataView input) |
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virtual [](start = 15, length = 7)
remove
glebuk
reviewed
Mar 25, 2019
| return Transformer; | ||
| } | ||
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| public virtual IDataView Transform(IDataView input) |
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virtual [](start = 15, length = 7)
remove virtual
glebuk
reviewed
Mar 25, 2019
| private protected readonly IHost Host; | ||
| [BestFriend] | ||
| private protected readonly TTransformer Transformer; | ||
| internal readonly TTransformer Transformer; |
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Transformer [](start = 39, length = 11)
not needed
glebuk
reviewed
Mar 25, 2019
| Host.CheckValue(input, nameof(input)); | ||
| // Validate input schema. | ||
| Transformer.GetOutputSchema(input.Schema); | ||
| return Transformer; |
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Transformer [](start = 19, length = 11)
return this.
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I am a bit concerned about the fact that we have to .Fit(...) for non trainable transforms. I think it can make ML.NET look really bad! I worked on a solution for the problem...
I tried three approaches:
For each one of these the difficult part is making sure that the estimator/transformer chains work properly. So I implemented a TrivialEstiamtorChain that mimics EstimatorChain but on the class TrivialEstimator instead of the interface IEstimator.
For 1. and 2. I did not manage to make it work... When you .Append() two trivialestimators it will just have a difficult time to distinguish whether you want to create a new EstimatorChain or a TransformerChain.
For 3. I managed to make it work, I think! The .Append() works and will switch to an EstimatorChain as soon as a trainable estimator is added to the pipeline.
Is it fine not having a class/interface that combines ITransformer and IEstimator?