What is underspecified meaning?

Filters. To give insufficient, or insufficiently precise, information: to specify incompletely.

What is underspecified model?

A regression model is underspecified if the regression equation is missing one or more important predictor variables. This situation is perhaps the worst-case scenario, because an underspecified model yields biased regression coefficients and biased predictions of the response.

Is underspecification a word?

Inadequate specification; failure to specify in enough detail. The underspecification of the project led to the development of software that was not fit for purpose.

What is underspecification in machine learning?

Underspecification is defined as the failure to specify in adequate detail. In the context of machine learning, underspecification implies that the training phase of a model can produce a good model. It can also produce a flawed model, and it would not tell the difference. As a result, we wouldn’t either.

What is underspecification machine learning?

Underspecification is defined as the failure to specify in adequate detail. In the context of machine learning, underspecification implies that the training phase of a model can produce a good model. It can also produce a flawed model, and it would not tell the difference.

Is underspecification a noun?

The underspecification of the project led to the development of software that was not fit for purpose. noun. (linguistics) A phenomenon in which certain features are omitted in underlying representations.

What is multicollinearity explain it with an example?

Multicollinearity generally occurs when there are high correlations between two or more predictor variables. Examples of correlated predictor variables (also called multicollinear predictors) are: a person’s height and weight, age and sales price of a car, or years of education and annual income.

What is underspecification in phonology?

In theoretical linguistics, underspecification is a phenomenon in which certain features are omitted in underlying representations. Restricted underspecification theory holds that features should only be underspecified if their values are predictable.

What is the definition of Mistakable?

Definition of mistakable : capable of being misunderstood or mistaken.

How do you explain multicollinearity?

Multicollinearity is the occurrence of high intercorrelations among two or more independent variables in a multiple regression model. In general, multicollinearity can lead to wider confidence intervals that produce less reliable probabilities in terms of the effect of independent variables in a model.