predictor

As nouns the difference between predictor and driver

is that predictor is something that anticipates, predicts or foretells while driver is one who drives something, in any sense of the verb to drive.

As a proper noun Driver is

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As nouns the difference between predictor and indicator

is that predictor is something that anticipates, predicts or foretells while indicator is a pointer or index that indicates something.

As nouns the difference between predicator and predictor

is that predicator is that which predicates; that designates a property or relationship while predictor is something that anticipates, predicts or foretells.

As a noun predictor

is something that anticipates, predicts or foretells.

As an adjective predictory is

serving to predict; predictive.

As nouns the difference between preditor and predictor

is that preditor is in the entertainment industry, a job title that combines both the duties of a producer and an editor, and depending on the skills of the individual, the duties of a producer, a writer and an editor or preditor can be while predictor is something that anticipates, predicts or foretells.

As nouns the difference between taxonomy and predictor

is that taxonomy is the science or the technique used to make a classification while predictor is something that anticipates, predicts or foretells.

As a noun predictor

is something that anticipates, predicts or foretells.

As a verb interessent is

.

As nouns the difference between independent and predictor

is that independent is a candidate or voter not affiliated with any political party, a free thinker, free of a party platform while predictor is something that anticipates, predicts or foretells.

As an adjective independent

is not dependent; not contingent or depending on something else; free.

As nouns the difference between predictor and multicollinearity

is that predictor is something that anticipates, predicts or foretells while multicollinearity is (statistics) a phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, so that the coefficient estimates may change erratically in response to small changes in the model or data.