Numerically-Labeled Learning Dataset

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.

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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.

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