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predictors and output of the model vs predictors and output

Both phrases are correct, but they are used in slightly different contexts. 'Predictors and output of the model' is more specific and refers to the predictors and output within the context of a model. On the other hand, 'predictors and output' is more general and can refer to predictors and output in any context.

Last updated: March 17, 2024 • 469 views

predictors and output of the model

This phrase is correct and commonly used in the context of discussing predictors and output within a model.

This phrase is used when referring to the specific predictors and output variables within a model or a predictive system.

Examples:

The predictors and output of the model need to be carefully analyzed.
Understanding the relationship between predictors and output of the model is crucial for accurate predictions.

Alternatives:

features and target of the model
independent variables and dependent variable of the model
input and output of the model
explanatory variables and response variable of the model
covariates and outcome of the model

predictors and output

This phrase is correct and can be used in a general context when referring to predictors and output without specifying a particular model.

This phrase is more general and can be used when discussing predictors and output variables in any context, not necessarily within a model.

Examples:

The study analyzed the relationship between predictors and output.
Predictors and output play a crucial role in data analysis.

Show examples from the web [+]

Dec 14, 2014 ... In simple terms, (i) in deterministic models, all input variables (predictors) and output variables (responses) are non-stochastic; an example is ...
be referred to as predictors and output-layer neurons as the criterion variable. However, an important difference is that predictors and the criterion variable are ...
Qualitative understanding of relationship between predictors and output. Filter out irrelevant features. Tackle Outliers. Decision Trees. Trees. Trees: Partition ...
Oct 7, 2013 ... ... algorithms (e.g. genetic programming) are often used to find mathematical relationships between input predictors and output response.

Alternatives:

input variables and output
independent variables and dependent variable
features and target
explanatory variables and response variable
covariates and outcome

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