All-Numeric Numeric-Value Prediction Task Input

An All-Numeric Numeric-Value Prediction Task Input is a regression task input for a numeric-predictors regression task (such as It can be an input for kernel regression, least-squares regression).

• Context:
  • It can (typically) include a Numeric-Predictors Numerically-Labeled Dataset.
    • [math]\displaystyle{ X=\{x_{i1},\,x_{i2},\,\ldots ,\,x_{ip}\,\} }[/math], a continuous dataset of observed values of one or more independent variables, these are called the predictor variables, regressors, exogenous variables, explanatory variables, covariates, input variables.
    • [math]\displaystyle{ Y=\{y_i\}^p_{i=1}=\{y_1,\,\ldots,\,y_p\} }[/math], a continuous dataset of observed values of the dependent variable. This is called the response variable, regressand, endogenous variable, measured variable, criterion variable.
  • It can (often) include a Regression Model Family, such as a linear model.
  • It can (often) include a Regression Loss Function, such as a least-squares loss function.
  • …
• Example(s):
  • the data for this sales prediction task
• Counter-Example(s):
  • a Categorical-Predictors Regression Task Input.
  • a Numeric-Predictors Classification Input.
• See: Numerically-Labeled Dataset, Regression Output.

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