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Given several related tasks, multi-task feature selection determines the importance of features by mining the correlations between them.
The observed variability could be due to attention to the task, or could be a feature of the relationship (e.g., degree of obsession with the partner, or strength of the relationship).
The target appeared among varying numbers of distractors that resembled another familiar television character and was either a uniquely colored shape (the feature search task) or a unique color-shape combination (the conjunction search task).
There's also a task list feature to keep track of who's doing what.
Therefore, the primary task for feature generation is the construction of features containing in-depth signal information that cannot be extracted or reconstructed otherwise.
Preprocessing is where text data is cleaned and processed via NLP tasks and is a preparatory task for feature processing.
We first consider the task of feature selection.
Another related task is feature selection that selects a small subset of discriminative features.
For the BioCreative 2012 Triage task, possible feature candidates, including both co-occurrence and network features, were examined and explored.
For the task of feature selection, data samples are randomly divided into two groups: training set and validation set.
Generally, the task of feature selection in classification issue is formally defined as the process of selecting the optimal feature subset S ⊆ X to have high classification performance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com