|
Class Summary |
| AbstractSeriesProcessing |
This is the abstract superclass for all series processing operators. |
| EnsureMonotonicity |
This operator filters out all examples which would lead to a non-monotonic behaviour of the specified attribute. |
| FillDataGaps |
This operator fills gaps in the data based on the ID attribute of the data set. |
| LabelTrend2Classification |
This operator iterates over an example set with numeric label and converts the
label values to either the class 'up' or the class 'down' based on whether the
change from the previous label is positive or negative. |
| MultivariateSeries2WindowExamples |
This operator transforms a given example set containing series data into a
new example set containing single valued examples. |
| Series2WindowExamples |
This is the superclass for all series to example transformation operators based on windowing. |
| SingleAttributes2ValueSeries |
Transforms all regular attributes of a given example set into a value series. |
| UnivariateSeries2WindowExamples |
This operator transforms a given example set containing series data into a
new example set containing single valued examples. |
| WindowExamples2ModelingData |
This operator performs several transformations related to time series predictions
based on a windowing approach. |