# Can I make an excel to predict with new input after have a training model ANN (Neural net)

Hi everyone,

I am in a problem to make an excel with the result after running and training model ANN Neural net in rapidminer.

I made an prediction task, using input with many numbers and labels, OUTPUT is a real number (REGRESSTION)

But when the result show the neural net with nodes and theirs weights, i dont know how to make an regresstion calculator by excel.

I see on the internet that when we use this for classifier rapidminer use active function (sigmoid) and when the predict result is regression, rapidminer will use linear .

I also think linear is this: Y (output) = W*x

w is the matrix of weights and x is the matrix of input.

Immo001 had 6 years ago.

Here is what he/she did, same as me:

"

HELP ME ANY BRO?

I am in a problem to make an excel with the result after running and training model ANN Neural net in rapidminer.

I made an prediction task, using input with many numbers and labels, OUTPUT is a real number (REGRESSTION)

But when the result show the neural net with nodes and theirs weights, i dont know how to make an regresstion calculator by excel.

I see on the internet that when we use this for classifier rapidminer use active function (sigmoid) and when the predict result is regression, rapidminer will use linear .

I also think linear is this: Y (output) = W*x

w is the matrix of weights and x is the matrix of input.

Immo001 had 6 years ago.

Here is what he/she did, same as me:

"

My process:

"Data" --> "x-validation"

In the "x-validation" is the "neural net" on the left side (training), "apply model" and "performance" is on the right side (testing).

In the end of x-validation is again "apply model" connected with multiply to the data.

Rapid miner shows in the input layer attribute 1, attribute 2 and a threshold node.

In the hidden layer are three noddes and a threshold node.

There is only one output node.

Descripted Result:

Node 1

1 att. -1.763

2 att. -1.144

Bias

Node 2

1 att. -1.776

2 att. -1.103

Bias -1.178

Node 3

1 att. -1.937

2 att. -1.937

Bias -0.996

Output

1 Node -1.389

2 Node -1.376

3 Node -1.495

Threshold 0.112

Rapid miner gives me also a predicted value for every row.

Now I want to use the first row of my dataset (att. 1 and 2) to recalculate the predicted result.

The Idea is, if i know how to recalculate I can calculate new data. Or use the formula in a Excel sheet. In my exapmle it is the turnover of a neu grocery store.

My calculations (1att. 0.532, 2. att 0.089, the predicted result is 0.341)

Node 1

0.532 * (-1.763) + 0.089 * (-1.144) + (-1.173) = -2,212

after the sigmoid transformation I get 0,098

Node 2

0.532 * (-1.776) + 0.089 * (-1.103) + (-1.178) = -2,220

after the sigmoid transformation I get 0,097

Node 3

0.532 * (-1.937) + 0.089 * (-1.254) + -0.996 = -2,137

after the sigmoid transformation I get 0,105

Then I do the linear regression. Im not sure if it is right. I dont know how to use the threshold value.

0,098 (-1.389)

0,097 (-1.376)

0,105 (-1.495)

I get a correlation coefficient of 0,999

but I expect 0.341 ????

Do you understand my problem?

I hope somebody can help me. If you need detail please ask me.

How can rapid miner predict the turnover of a new grocery store (att. 1+ 2, but without a label/turnover)?

I appreciate your help.

Greeting Immo001

""Data" --> "x-validation"

In the "x-validation" is the "neural net" on the left side (training), "apply model" and "performance" is on the right side (testing).

In the end of x-validation is again "apply model" connected with multiply to the data.

Rapid miner shows in the input layer attribute 1, attribute 2 and a threshold node.

In the hidden layer are three noddes and a threshold node.

There is only one output node.

Descripted Result:

Node 1

1 att. -1.763

2 att. -1.144

Bias

Node 2

1 att. -1.776

2 att. -1.103

Bias -1.178

Node 3

1 att. -1.937

2 att. -1.937

Bias -0.996

Output

1 Node -1.389

2 Node -1.376

3 Node -1.495

Threshold 0.112

Rapid miner gives me also a predicted value for every row.

Now I want to use the first row of my dataset (att. 1 and 2) to recalculate the predicted result.

The Idea is, if i know how to recalculate I can calculate new data. Or use the formula in a Excel sheet. In my exapmle it is the turnover of a neu grocery store.

My calculations (1att. 0.532, 2. att 0.089, the predicted result is 0.341)

Node 1

0.532 * (-1.763) + 0.089 * (-1.144) + (-1.173) = -2,212

after the sigmoid transformation I get 0,098

Node 2

0.532 * (-1.776) + 0.089 * (-1.103) + (-1.178) = -2,220

after the sigmoid transformation I get 0,097

Node 3

0.532 * (-1.937) + 0.089 * (-1.254) + -0.996 = -2,137

after the sigmoid transformation I get 0,105

Then I do the linear regression. Im not sure if it is right. I dont know how to use the threshold value.

0,098 (-1.389)

0,097 (-1.376)

0,105 (-1.495)

I get a correlation coefficient of 0,999

but I expect 0.341 ????

Do you understand my problem?

I hope somebody can help me. If you need detail please ask me.

How can rapid miner predict the turnover of a new grocery store (att. 1+ 2, but without a label/turnover)?

I appreciate your help.

Greeting Immo001

HELP ME ANY BRO?

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