Linear regression prediction don't match with the model

PlatyQ

Hello

This time I have a question about linear regression operator.

There is my process: I want predict a value (AverageW) with 3 parameters (Layers, WFS, TS) and observe the model choose by the operator.

<运营商激活= " true "类=“检索”兼容ibility="8.2.000" expanded="true" height="68" name="Retrieve TS50+80" width="90" x="45" y="34">

The problem is that I obtain a prediction that don't match with the result that I obtain with coefficients give by the model.

For example to coefficients:

coef_Layer = 0.150;

coef_TS = -0.045;

coef_WFS = 1.150;

intercept = 2.488 ;

And example Layer=2 ; TS= 50; WFS= 3
I compute Layer*coef_Layer + coef_TS*TS + coef_WFS*WFS + intercept = 3,988

but the model predict 3.968 to this example!

It is not a big difference but I need to understand if I forget a parameter "epsilon" or other.

I hope somebody can help me because I don't find a answer in documentation (And it is not the first time I have question about documentation)

My data are in the table below if there are problems with csv file:

(I remove not used column so select attributes is not useful)

Spoiler

Layers	WFS	TS	AverageW
1	3	50,0	3,0
1	4	50,0	4,0
1	5	50,0	4,1
1	6	50	7,2
2	3	50,0	3,9
2	4	50,0	4,9
2	5	50,0	5,3
2	6	50,0	7、5
3	3	50	4,3
3	4	50,0	5,4
3	5	50,0	5,8
3	6	50,0	7、6
5	3	50,0	4,5
5	4	50	6,3
5	5	50,0	6,9
5	6	50,0	10,8
10	3	50,0	5,0
10	4	50,0	6,7
10	5	50	8,1
20	3	50,0	5,5
20	4	50,0	7,3
20	5	50,0	9,1
1	3	80,0	2,4
1	4	80,0	3,7
1	5	80,0	3,7
1	6	80,0	4,7
2	3	80,0	3,1
2	4	80,0	4,1
2	5	80,0	4,1
2	6	80,0	5,8
3	3	80,0	3,3
3	4	80,0	4,0
3	5	80,0	4,5
3	6	80,0	6,9
5	3	80,0	3,7
5	4	80,0	4,6
5	5	80,0	5,1
5	6	80,0	6,9
10	3	80,0	3,8
10	4	80,0	5,2
10	5	80,0	6,4

Thank you in advance

lionelderkrikor

Hi@PlatyQ,

In reality the displayed coefficients are rounded :

So if you perform the calculus with the precise numbers, you obtain3.968:

Regards,

Lionel

PlatyQ

@lionelderkrikor

thank, I never running the mouse over the table enough time to see precise numbers.

Thank you!