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Discover LudwigThe phrase "aggregated feature" is correct and usable in written English.
It can be used in contexts related to data analysis, machine learning, or software development, where multiple characteristics or data points are combined into a single representation.
Example: "The model's performance improved significantly after incorporating the aggregated feature derived from user behavior data."
Alternatives: "combined attribute" or "consolidated characteristic".
Exact(1)
The coordination service computes an aggregated feature vector for each preexisting sub-region describing properties common to all VMs within that sub-region.
Similar(58)
Aggregating feature counts provided adequate feature density and reduced the dimensionality without discarding features that could be informative.
There are a number of ways to reduce dimensionality and increase feature set density, such as clustering similar features [ 35- 37], removing features with low information content [ 38], reducing the number of class labels [ 28], and aggregating feature counts.
The features are associated to products to aggregate features opinions for products also.
Moreover, the vertical pooling could obtain the completed and spatial information by aggregating features across all the feature maps.
Gradient boosting decision trees are explored to aggregate features on segmented regions using a supervised training manner.
Methods are often employed to assist various algorithms make the best use of features by aggregating features or creating new features based on existing data.
The clustering representatives from GMM are encoded via a multi-layout Fisher vector (MFV) instead of traditional Fisher vector (FV) to aggregate features based on their spatial information.
The authors chose to utilize local statistical features so that these features aggregated in feature space.
The feature vector is built in two steps: first, it calculates feature vectors for specific pocket atoms (AFVs) which are then aggregated into feature vectors of the inner points (IFVs).
The SCM preserves the spatial information because the pooling operation is conducted across all the feature maps, while the other traditional pooling operations aggregate one feature map into a feature.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com