"How to Setup Value Series Feature Extraction Operator with Windowing Operator"
Hi all,
I trying to use Series Extension to perform classification on multivariate time series data. So far, I have been able get sliding window using the 'Windowing" operator (encode series by examples)
Example of source data:
point1 point2 point3 label
a1 b1 c1 class1
a2 b2 c2 class1
a3 b3 c3 class1
... .... ... ........
Since I wish to perform classification on these data points. I intend to extract features based on the sliding window and then have dataset similar to the example below (assume window size=2)
Point1-1 Point1-0 Point1-Extracted-Feat. Point2-1 Point2-0 Point2-Extracted-Feat. Point3-1 Point3-0 Point3-Extracted-Feat label
a1 a2 XXXXXX b1 b2 XXXXXXX c1 c2 XXXXXXXX Class1
a3 a4 XXXXXX b3 b4 XXXXXXX c3 c4 XXXXXXX Class1
... ... ......
With this approach, I can select the extracted features as attributes for the classification process.
So far, I have only been able to get the attributes (Point1-1, Point1-0, Point2-1, Point2-0, Point3-1, Point3-0) using the window operator. But when I attempt to use the operators such as Discrete Wavelet Transformation, it only operated on the first example (i.e a1, a2, b1, b2, c1,c2). I also had to use the "Data to Series"Operator to be able to use any of the extraction or transformation operator for series. I don't know if I am using the write approach.
What is the best setup for this approach?
What is the best setup for using sliding window and extracting features to give a similar dataset similar to the example I showed above.
Best Regards
/Sam
I trying to use Series Extension to perform classification on multivariate time series data. So far, I have been able get sliding window using the 'Windowing" operator (encode series by examples)
Example of source data:
point1 point2 point3 label
a1 b1 c1 class1
a2 b2 c2 class1
a3 b3 c3 class1
... .... ... ........
Since I wish to perform classification on these data points. I intend to extract features based on the sliding window and then have dataset similar to the example below (assume window size=2)
Point1-1 Point1-0 Point1-Extracted-Feat. Point2-1 Point2-0 Point2-Extracted-Feat. Point3-1 Point3-0 Point3-Extracted-Feat label
a1 a2 XXXXXX b1 b2 XXXXXXX c1 c2 XXXXXXXX Class1
a3 a4 XXXXXX b3 b4 XXXXXXX c3 c4 XXXXXXX Class1
... ... ......
With this approach, I can select the extracted features as attributes for the classification process.
So far, I have only been able to get the attributes (Point1-1, Point1-0, Point2-1, Point2-0, Point3-1, Point3-0) using the window operator. But when I attempt to use the operators such as Discrete Wavelet Transformation, it only operated on the first example (i.e a1, a2, b1, b2, c1,c2). I also had to use the "Data to Series"Operator to be able to use any of the extraction or transformation operator for series. I don't know if I am using the write approach.
What is the best setup for this approach?
What is the best setup for using sliding window and extracting features to give a similar dataset similar to the example I showed above.
Best Regards
/Sam