Difference between revisions of "Orange: Moving Transform"
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Onnowpurbo (talk | contribs) (Created page with "Sumber: https://orange.biolab.si/widget-catalog/time-series/moving_transform/ Apply rolling window functions to the time series. Use this widget to get a series’ mean. I...") |
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In this widget, you define what aggregation functions to run over the time series and with what window sizes. | In this widget, you define what aggregation functions to run over the time series and with what window sizes. | ||
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| + | [[File:Moving-transform-stamped.png|center|200px|thumb]] | ||
Define a new transformation. | Define a new transformation. | ||
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In the case of non-overlapping windows, define the fixed window width(overrides and widths set in (4). | In the case of non-overlapping windows, define the fixed window width(overrides and widths set in (4). | ||
| − | Example | + | ==Example== |
To get a 5-day moving average, we can use a rolling window with mean aggregation. | To get a 5-day moving average, we can use a rolling window with mean aggregation. | ||
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| + | [[File:Moving-transform-ex1.png|center|200px|thumb]] | ||
To integrate time series’ differences from Difference widget, use Cumulative sum aggregation over a window wide enough to grasp the whole series. | To integrate time series’ differences from Difference widget, use Cumulative sum aggregation over a window wide enough to grasp the whole series. | ||
| − | + | [[File:Moving-transform-ex2.png|center|200px|thumb]] | |
Revision as of 07:07, 26 January 2020
Sumber: https://orange.biolab.si/widget-catalog/time-series/moving_transform/
Apply rolling window functions to the time series. Use this widget to get a series’ mean.
Inputs
Time series: Time series as output by As Timeseries widget.
Outputs
Time series: The input time series with the added series’ transformations.
In this widget, you define what aggregation functions to run over the time series and with what window sizes.
Define a new transformation. Remove the selected transformation. Time series you want to run the transformation over. Desired window size. Aggregation function to aggregate the values in the window with. Options are: mean, sum, max, min, median, mode, standard deviation, variance, product, linearly-weighted moving average, exponential moving average, harmonic mean, geometric mean, non-zero count, cumulative sum, and cumulative product. Select Non-overlapping windows options if you don’t want the moving windows to overlap but instead be placed side-to-side with zero intersection. In the case of non-overlapping windows, define the fixed window width(overrides and widths set in (4).
Example
To get a 5-day moving average, we can use a rolling window with mean aggregation.
To integrate time series’ differences from Difference widget, use Cumulative sum aggregation over a window wide enough to grasp the whole series.
