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SCENARIO 14-6 the Neural Network Output Below Was Obtained for Predicting the Predicting

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SCENARIO 14-6
The neural network output below was obtained for predicting the weekend box office revenue of a newly released movie (in thousands of dollars) based on data collected in different cities on the expenditure (at $25, $30, $35, $40, $45, $50, $55, $60 $65 or $70 thousands) spent on TV advertising and the number of times (10, 15, 20, 25, 30 or 35) a day the advertisement appear on TV. SCENARIO 14-6 The neural network output below was obtained for predicting the weekend box office revenue of a newly released movie (in thousands of dollars) based on data collected in different cities on the expenditure (at $25, $30, $35, $40, $45, $50, $55, $60 $65 or $70 thousands) spent on TV advertising and the number of times (10, 15, 20, 25, 30 or 35) a day the advertisement appear on TV.   -Referring to SCENARIO 14-6, how many hidden nodes are used in the neural network model?
-Referring to SCENARIO 14-6, how many hidden nodes are used in the neural network model?


Definitions:

Dimensions Locating

The process of defining and marking the exact locations of features on manufactured parts, crucial for their proper assembly and function.

Target Areas

Specific regions designated for attention or action in a project or on a drawing.

Datum Feature

A reference point, axis, or plane from which dimensions are measured, providing a starting point for the geometric control of a part.

Datum Target Point

A specific point, line, or area on a part that serves as a reference or starting point for geometric measurements.

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