Machine Learning Dataset
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A Machine Learning Dataset is a dataset used in a machine learning task.
- Context:
- It can range from being a Numerical ML Dataset to being a Categorical ML Dataset.
- It can range from being an Unlabeled ML Dataset to being a Labeled ML Dataset.
- It can range from being a Single-Predictor Learning Dataset (such as a univariate timeseries) to being a Multi-Predictor Learning Dataset.
- It can be a output to a Learning Record Set Creation Task.
- It can range from being a Training Dataset to being an Evaluation Dataset.
- Example(s):
- a Training Dataset,
- an Evaluation Dataset,
- a Holdout Set.
- a POS Learning Record Set.
- …
- Counter-Example(s):
- See: Data Record Set, User-Interaction Data.
References
2017
- (Sammut & Webb, 2017) ⇒ (2017) "Data Set". In: Sammut & Webb, 2017.
- QUOTE: A data set is a collection of data used for some specific machine learning purpose. A training set is a data set that is used as input to a learning system, which analyzes it to learn a model. A test set or evaluation set is a data set containing data that are used to evaluate the model learned by a learning system. A training set may be divided further into a growing set and a pruning set. Where the training set and the test set contain disjoint sets of data, the test set is known as a holdout set.