Script gaussian_generator/main.py was used to generate time series with 12 dimensions. First ten rows are training vectors with gaussian distribution, five next are testing vectors that are anomalies and last five are testing vectors with gaussian distribution.
Results for file data.txt are:
zscore for anomalies:
4.969487 4.657071 7.081843 5.540407 4.656935 6.303215 4.027134 5.066305 7.845419 6.445864 5.210669 4.778178
5.017699 5.173791 6.893960 5.504921 4.963943 6.082908 4.460260 4.589011 7.845419 6.197362 5.881950 4.369143
5.379292 4.525143 7.256306 4.984473 4.839221 5.617816 3.989471 4.391108 8.208559 6.625338 4.932023 5.154922
4.969487 4.613095 7.752854 5.635034 4.618558 5.972755 4.469676 4.367826 8.698009 5.796998 4.754703 4.573661
5.656512 4.635083 6.920801 5.717832 4.896785 5.605577 3.735245 4.274694 7.482278 6.031694 5.919947 5.101101
zscore for proper values:
0.714748 0.534310 0.063075 0.951001 -0.696526 -0.416135 0.317312 -0.218857 1.119421 0.343761 -0.514227 -0.334763
0.353155 0.710214 2.559234 1.755329 1.481316 1.909323 0.449133 -0.731075 -1.706762 0.895988 -1.540149 -0.991372
-0.683410 -1.895371 -0.044287 -0.290978 1.356594 -2.007237 -0.247635 -1.301500 0.898379 -0.056603 0.448366 0.354138
-1.466860 0.820155 -0.191909 0.548836 0.013432 -0.820030 0.646865 -1.953414 2.429885 2.400805 0.195052 -0.022605
-1.683816 -0.598075 1.700340 -2.644822 0.761765 1.089293 -0.388872 -0.940619 -0.222621 0.440401 0.777674 -0.054897