# Time windows

Hello.

I have a lot of data that I want to pretreat before I use them in machine learning. I have time stamps on all my attributes, and would like to make time windows - all data within 5 min for example, must be assembled, and the mean of these data is the new value. This must then be repeated for all the data I have, so I end up with a lot of windows on 5 min each. Thus, I should like to end up with far fewer data points.

Is this possible in Rapid Miner?

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## Answers

3,453RM Data ScientistHi Mathias,

yes it is. The key operator is Windowing in the Time Series extension. You can combine this with Generate Aggregation.

~Martin

Dortmund, Germany

20MavenI am not sure that the operator Windowing do what I need.

I have made this muckup of what I'm trying to achieve; http://imgur.com/a/exoJj

Basically, I need to make a window every five minutes, in which all values within this window is assembled and a mean value calculated from these.

3,453RM Data ScientistHi,

isnt that a moving average and you simply use the Moving Average operator?

~Martin

Dortmund, Germany

20MavenWith moving average I end up with the same number of examples - i want to combine all exsamples within a 5 minute window and take the mean value of that window. Then I want to do the same for the next 5 minutes.

So no matter if I got 10 examples or 100 exsamples within a 5 min window, it should all be combined to a single mean value.

20MavenOkay, I have come to the conclusion that I can use the operator Windowing and generate aggregation.

Now I divide column A in 180 new columns, then I use generate aggregation to find the mean value of the 180 columns. However, I also need to know whether the value is increasing or decreasing in the 180 columns, and I can not get generate aggregation to do this?

Like what LINEST do in excel.

Is there amy way I can do this?

Thank you in advance!

3,453RM Data ScientistSo, you would like to fit a line on it and get the coefficents? Thats one of the extract operators of time series.

Dortmund, Germany

20MavenI've tried the operator Extract Coefficients, but requires series data where I work with ExsampleSet. I've tried to convert the data with the operator Data to series, but then I can only use one attribute (and I now have 180 attributes due to operator windowing)

1,635UnicornI think the "Fit Trend" operator from the Series extension will do what you are looking for--it uses an inner modeling operator, so if you want a simple linear estimate you just use the linear regression model, or you can use other modeling algorithms if you want something more complex.

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