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ChangeFinder Anomaly and Change-Point Detector #305
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…etected. Removed -dim option accordingly. Also changed some initial parameter values and minutiae in ChangeFinderUDFTest, and fixed a typo in MathUtils.
Implemented multiple passes for multidimensional covariances to ensure they are full-rank. Changed internals of solving the system of equations from Cholesky Decomposition to LU Decomposition (However, after the multiple changes introduced in this commit, Cholesky Decomposition may be viable again.)
- Pretty comments describing the computation process in more detail. - Using the initial values of the data to break in data structures instead of rand. (Random generation tends to unpredictably reduce detection accuracy in the beginning.) - Added a moving average for change-point scores to improve detection accuracy. - Refactored tests
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@L3Sota It seems unit tests of ChangeFinder is failing. |
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@myui OK, will look into it. |
The Java 7 Double class doesn't have a isFinite(double) method. Using isNaN(double) instead.
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@L3Sota Thanks for fixing ^. |
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@L3Sota I'm revising your ChangeFinder implementation in Could you check it in your spare time? |
| */ | ||
| RealMatrix[][] xCovarsCombinedRaw = | ||
| new RealMatrix[xRunningWindowSize][xRunningWindowSize]; | ||
| for (int i = 0; i < xRunningWindowSize; i++) { |
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@L3Sota It seems Toeplitz matrix initialization has a bug. Fixed in
https://github.com/myui/hivemall/blob/feature/changefinder1d/core/src/main/java/hivemall/utils/math/MatrixUtils.java#L118
OK, will take a look at it. |
Merged
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Let's continue discussions on #333 |
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Statistical Anomaly and Change-Point detection of discrete time series data via fitting to an SDAR (Sequentially Discounting Autoregressive) Model.
Input
Takes a single n-dimensional vector of doubles as the next point in the time series. Multiple calls automatically update the internal SDAR model.
Output
A struct containing the following 4 elements:
Notes
a + ccalls after initialization usually return false positives, whereaandcare the value of the optionsaWindowandcWindow, respectivelyArticles/Slides (Japanese):