Machine learning data cleaning
An information handling system may be configured to: receive time-series data regarding measurements of a physical variable; determine that a missing data point is missing from the time-series data, wherein the missing data point corresponds to a particular day of the week; in response to a determination that earlier corresponding data from the particular day of the week of an earlier week is available, copy the earlier corresponding data to replace the missing data; in response to a determination that later corresponding data from the particular day of the week of a later week is available, copy the later corresponding data to replace the missing data; and in response to a determination that neither the earlier corresponding data nor the later corresponding data is available, perform interpolation to replace the missing data.
1. An information handling system comprising:
at least one processor; and
a non-transitory memory coupled to the at least one processor;
wherein the information handling system is configured to:
receive time-series data regarding measurements of a physical variable;
determine that a missing data point is missing from the time-series data, wherein the missing data point corresponds to a particular day of the week;
in response to a determination that earlier corresponding data from the particular day of the week of an earlier week is available, copy the earlier corresponding data to replace the missing data;
in response to a determination that later corresponding data from the particular day of the week of a later week is available, copy the later corresponding data to replace the missing data; and
in response to a determination that neither the earlier corresponding data nor the later corresponding data is available, perform interpolation to replace the missing data.
2. The information handling system of claim 1 , wherein the time-series data comprises telemetry data of a target information handling system.
3. The information handling system of claim 2 , wherein the telemetry data relates to a variable selected from the group consisting of: temperature, fan speed, vibration level, CPU utilization, memory utilization, and disk utilization.
4. The information handling system of claim 2 , wherein the telemetry data is received from a software agent executing on the target information handling system.
5. The information handling system of claim 1 , wherein the information handling system is further configured to determine that the missing data is of a missing completely at random (MCAR) type.
6. The information handling system of claim 5 , wherein the determination of the MCAR type is based on a user input.
7. A method comprising:
an information handling system receiving time-series data regarding measurements of a physical variable;
the information handling system determining that missing data points are missing from the time-series data, wherein the missing data points correspond to particular days of the week; and
for each missing data point of the missing data points, the information handling system:
in response to a determination that earlier corresponding data from the particular day of the week of an earlier week is available, copying the earlier corresponding data to replace the missing data;
in response to a determination that later corresponding data from the particular day of the week of a later week is available, copying the later corresponding data to replace the missing data; and
in response to a determination that neither the earlier corresponding data nor the later corresponding data is available, performing interpolation to replace the missing data.
8. The method of claim 7 , further comprising removing data points from the time-series data that have negative values.
9. The method of claim 7 , wherein the time-series data comprises telemetry data of a target information handling system.
10. The method of claim 9 , wherein the telemetry data relates to a variable selected from the group consisting of: temperature, fan speed, vibration level, CPU utilization, memory utilization, and disk utilization.
11. The method of claim 9 , wherein the telemetry data is received from a software agent executing on the target information handling system.
12. The method of claim 7 , further comprising determining that the missing data is of a missing completely at random (MCAR) type.
13. The method of claim 12 , wherein the determination of the MCAR type is based on a user input.
14. An article of manufacture comprising a non-transitory, computer-readable medium having computer-executable code thereon that is executable by an information handling system for:
receiving time-series data regarding measurements of a physical variable;
determining that a missing data point is missing from the time-series data, wherein the missing data point corresponds to a particular day of the week;
in response to a determination that earlier corresponding data from the particular day of the week of an earlier week is available, copying the earlier corresponding data to replace the missing data;
in response to a determination that later corresponding data from the particular day of the week of a later week is available, copying the later corresponding data to replace the missing data; and
in response to a determination that neither the earlier corresponding data nor the later corresponding data is available, performing interpolation to replace the missing data.
15. The article of claim 14 , wherein the time-series data comprises telemetry data of a target information handling system.
16. The article of claim 15 , wherein the telemetry data relates to a variable selected from the group consisting of: temperature, fan speed, vibration level, CPU utilization, memory utilization, and disk utilization.
17. The article of claim 15 , wherein the telemetry data is received from a software agent executing on the target information handling system.
18. The article of claim 14 , wherein the information handling system is further configured to determine that the missing data is of a missing completely at random (MCAR) type.
19. The article of claim 18 , wherein the determination of the MCAR type is based on a user input.