Which of the following is a best practice when choosing a UiPath ML (Machine Learning) Extractor?
A.
The popularity of the ML Extractor among other UiPath users should be the primary factor. Opt for the ML Extractor that has the highest number of downloads or positive reviews.
B.
Consider the document types, language, and data quality. It is important to select one that is specifically trained or optimized for the document types being processed. It is also important to takeinto account the quality and diversity of the training data used to train the ML Extractor to ensure accurate and reliable extraction results.
C.
The size of the ML Extractor is the most important factor to consider. Bigger models always perform better and provide more accurate extraction results because the development team invested time and effort into creating the algorithm, which in turn will result in better performance for the trained model.
D.
The cost of the ML Extractor should be the main consideration. Select the ML Extractor that offers the lowest price, regardless of its performance or suitability for the specific document understanding needs.
The best practice is to select an ML Extractor based on document types, language, and data quality. Choosing a model specifically optimized for the type of document being processed ensures higher accuracy and reliability. The quality and diversity of the training data used to develop the model play a significant role in its performance.
[Reference: UiPath ML Extractors, , ]
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