| CPC G06F 11/0793 (2013.01) [G06F 11/0709 (2013.01); G06F 11/079 (2013.01)] | 26 Claims |
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1. A computer-implemented method executed by data processing hardware of a cloud database system that causes the data processing hardware to perform operations comprising:
receiving a point data anomaly detection query from a user, the point data anomaly detection query requesting the data processing hardware to determine a quantity of anomalous point data values in a set of point data values; and
in response to receiving the point data anomaly detection query:
training, using unsupervised learning, a model using the set of point data values;
for at least one respective point data value in the set of point data values:
determining, using the trained model, a variance value for the at least one respective point data value;
determining that the variance value satisfies a threshold value; and
determining that the at least one respective point data value is an anomalous point data value based on the variance value satisfying the threshold value; and
reporting the determined anomalous point data value to the user.
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