Regression finds out the model parameters which produces the least square error between - A. input value and output value B. input value and target value C. output value and target value D. model parameters and output value
Question
Regression finds out the model parameters which produces the least square error between - A. input value and output value B. input value and target value C. output value and target value D. model parameters and output value
Solution
The correct answer is C. output value and target value.
In regression analysis, the aim is to find the best fit line or curve for the given data points. This is done by minimizing the sum of the squared differences (also known as the least square error) between the predicted output value (from the model) and the actual target value.
Here's a step-by-step explanation:
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A regression model is created based on the input data. This model has certain parameters that define it.
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The model is used to predict the output values based on the input values.
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These predicted output values are then compared with the actual target values. The difference between these values is calculated.
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The squares of these differences are then summed up to give the least square error.
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The aim is to adjust the model parameters in such a way that this error is minimized.
So, the least square error is between the output value (predicted by the model) and the target value (actual value).
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