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In this market, do customers care about a large number of features?
Classification with thousands of classes and a large number of features is often computationally intractable.
Building such models involves a multitude of decisions, and the large number of features that need to be taken into account can overwhelm the researcher.
The thing that we notice here is that in order to use discriminate these kinds of features, we actually need as very large number of features, not few.
The proposed approach is applicable when the objects to be classified are characterized by a large number of features while a few train samples are available.
The algorithm developed removed a large number of features from the original data sets without reducing the classification accuracy of the committees.
The relative strengths of computational pathology include the ability to objectively assess and quantify a large number of features (far more than would be possible for a human researcher) in a systematic and high-throughput fashion.
Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a very large number of features, training examples, or both.
I can quibble that the large number of features means that some controls are hidden on drop-down menus behind unlabeled arrows, so trying to find that control you used before can be annoying.
It's missing a large number of features, some half implemented, others not at all.
A large number of features generally results in inconsistency in modeling the state distribution.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com