Numerically-Labeled Learning Dataset
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A Numerically-Labeled Learning Dataset is a labeled learning dataset with a numeric target attribute.
- Context:
- It can range from being a All-Numeric-Predictors Regression Dataset to being a Heterogenous-Predictors Numerically-Labeled Learning Dataset to being a Categorical-Predictors Numerically-Labeled Learning Dataset.
- It can (often) be an Supervised Regression Task Input (split into numerically-labeled training data and numerically-labeled testing data).
- Example(s):
- a All-Numeric-Predictors Regression Dataset, such as: sklearn's Boston dataset and for a Music Data YearPredictionMSD Task.
- a Heterogeneous-Predictors Regression Dataset, such as [1].
- a Categorical-Predictors Regression Dataset, such as ...
- …
- Counter-Example(s):
- a Category Labeled Dataset, such as the Fisher's Iris dataset.
- See: Numeric Target, Regression Task.
References
2011
- http://code.google.com/apis/predict/docs/glossary.html
- QUOTE: Regression Data - Training data that assigns numeric values to individual examples. Regression models enable the API to predict numeric values based on examples. For example, to return a predicted temperature, based on prior temperature entries.