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# How to make an actual prediction?

Let's say I have a dataset with 10 data points x0 ... x9, and I wish to predict the value for x11.

Using the windowing operator with window_size 3 and horizon 2 I get the training dataset below.

This dataset is fine, I can use a learner to learn a model, that can forecast the value for x11.

Label x-2 x-1 x-0

-----------------------------

x4 x0 x1 x2

x5 x1 x2 x3

x6 x2 x3 x4

x7 x3 x4 x5

x8 x4 x5 x6

x9 x5 x6 x7

But in order to make a prediction for x11 I not only need a model, I also need the appropriate model input.

This input data point would be:

Label x-2 x-1 x-0

-----------------------------

? x7 x8 x9

so this means I will have to fill my input data point with many more values.

Using the windowing operator with window_size 3 and horizon 2 I get the training dataset below.

This dataset is fine, I can use a learner to learn a model, that can forecast the value for x11.

Label x-2 x-1 x-0

-----------------------------

x4 x0 x1 x2

x5 x1 x2 x3

x6 x2 x3 x4

x7 x3 x4 x5

x8 x4 x5 x6

x9 x5 x6 x7

But in order to make a prediction for x11 I not only need a model, I also need the appropriate model input.

This input data point would be:

Label x-2 x-1 x-0

-----------------------------

? x7 x8 x9

Of course it is possible to generate this data point by hand, but in a more realistic scenario my dataset will have many more attributes, and my window_size will be much bigger,

How do I make Rapid Miner generate this input data point?

so this means I will have to fill my input data point with many more values.

0

## Answers

2,531Unicornwell, in an online scenario you will always have a different input than in an offline learning scenario. But applying this online in an productive enviroment needs many other changes, so that forming a correct example set should not be the biggest problem, is it?

Greetings,

Sebastian

537MavenI'm predicting the weather near my house, not sure if you call this "productive" :P

I manage to create the input I need, but its rather cumbersome.

Also a prediction can be rather insightful, if its producing all 0's for tomorrows temperature something is wrong! :P

This find led me to changing some parameters, so it actually makes a more sensible predictions now.

6Contributor IIIf got a data set with values for each month, from january 2000 till december 2009 and i want an actual result for january 2010 !

Thanks

3Contributor II have an Excel sheet with positive values from 0 to 9 ordered by date and I want to predict the number for the next day. I used Windowing, Sliding Window Validation, Support Vector Machine and I came closely to the result in every row but in the LAST row (where the prediction label is) it outputs 0 and it doesn't "predict".

I tried with another sheet with last date + 1 with the number that had to be "predicted" and the model works ok but for last_date + 2, again... 0!!!

What am I doing wrong?

Thanks in advance