Hey Pavol,
this is great - congratulations!
On 21 Apr 2016, at 8:30, Pavol Loffay wrote:
Hello Everyone,
I am happy to announce first release 0.1.0.Final of Hawkular Data
Mining.
Release contains several time series models and utility classes for
time
series modelling:
*Time series models*
- Simple exponential smoothing
- Double exponential smoothing (Holt's linear trend)
- Seasonal triple exponential smoothing (Holt Winters)
- Simple moving average (Weighted moving average)
- AutomaticForecaster - which automatically selects the best model
- All these models are estimated using maximum likelihood
estimation and
available for online learning
Time series manipulation & Statistics
- Augmented Dickey-Fuller test
- Autocorrelation function (ACF)
- Time series decomposition
- Time series lagging
- Time series differencing
- Automatic period identification
If you want to try it with Hawkular:
https://goo.gl/R93k02
1. clone
https://github.com/hawkular/hawkular/tree/datamining -
hawkular/hawkular branch datamining
2. build with -Pdev && run
3. enable predictions preferably for every metric
https://github.com/hawkular/hawkular-datamining and wait for some
time
(see below)
4. go to the Explorer tab, choose metric and increase forecasting
horizon
Data Mining is currently not able to query historical metric data from
metrics due to authentication issues. However it still receives
metrics
from bus so it is important to enable predictions as soon as possible
and
wait for some time to collect data (or increase collection interval).
This
will be fixed in the next versions.
Thanks to Jiri Kremser and UI team for helping with predictive charts.
Useful links:
- Docs
<
http://www.hawkular.org/docs/components/datamining/index.html>
- REST API <
http://www.hawkular.org/docs/rest/rest-datamining.html>
Regards
Pavol
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