Sergey, https://github.com/rhyolight/nupic/tree/super-hotgym/examples/opf/clients/hotgym/prediction
This is very undocumented and still a work in progress. For CLI commands and options, run "python run.py --help". Simple steps would be: > ./run.py generate_data > ./run.py swarm --input=local_data/Balgowlah_Platinum.csv > ./run.py run --name="Balgowlah Platinum" --plot (If you don't have matplotlib installed, omit the --plot option and predictions are written to disk.) --------- Matt Taylor OS Community Flag-Bearer Numenta On Sun, Apr 20, 2014 at 11:30 PM, Sergey Bryukov <[email protected]> wrote: > Hi Matt, thanks for afforts > > please send me branch name in case you have something already. Would like > to help sow how. > > Also it would be grate to show multidimensional records usage. > > Sergey > > > On 20.04.2014 20:31, Matthew Taylor wrote: > > Sergey, thanks for your questions. I am in the process of updating these > examples, so getting your questions now is useful. I'm working on the > prediction example, and will move to the anomaly detection example > afterwards. > > Unfortunately, I think there are some error with that example. It > doesn't look like the "aggregationInfo" section of the model_params is > being used at all. In fact, if you simple remove that block of > configuration, the example runs with exactly the same results. > > I can at least answer a couple of your questions regarding aggregation. > The aggregationInfo section specifics how input data will be aggregated, > and this requires an aggregation function. Aggregating data is kindof like > summarizing it and making it smaller, so in order to do this there must be > a function applying to a set of data to turn it into one value. That's what > the 'sum' and 'first' mean. 'First' means to simply take the first value in > the set of input data to use as the representative within the aggregate > data set. This works best with temporal values, for example if you have > values every 5 minutes, but you just want 15 minute aggregate data, you > want to use the first time value in the data set to signify that time > period. The 'sum' is just the sum of all data fields within the data. I > imagine there is also a 'mean' or 'avg'. > > I'll be getting deeper into this once I'm finished with > https://github.com/numenta/nupic/issues/548 and provide a better tutorial > for anomaly detection with the hotgym data set. > > Regards, > > --------- > Matt Taylor > OS Community Flag-Bearer > Numenta > > > On Wed, Apr 16, 2014 at 2:50 AM, Sergey Bryukov <[email protected]>wrote: > >> Hello, >> >> Im extending hotgym_anomaly example for multi denominational records and >> have question on how to fill MODEL_PARAMS correctly >> >> Let's assume we have fields: timestamp, (float)P0, (float)P1 >> >> 1. what is the place for P0 and P1 in below structure? What means 'sum' >> and 'first' >> >> 'aggregationInfo': { 'days': 0, >> 'fields': [(u'P0', 'sum'), (u'P0', 'first')], >> 'hours': 0, >> 'microseconds': 0, >> 'milliseconds': 0, >> 'minutes': 0, >> 'months': 0, >> 'seconds':1, >> 'weeks': 0, >> 'years': 0 >> } >> >> >> 2. I need encode only seconds, how to set encoder properly for timestamp? >> And what fields mean for P0: 'clipInput' 'maxval', 'minval', 'n', 'w' >> >> 'encoders': { u'timestamp_timeOfDay': { 'fieldname': u'timestamp', >> 'name': u'timestamp_timeOfDay', >> 'timeOfDay': (21, 0.5), >> 'type': 'DateEncoder' >> }, >> u'timestamp_dayOfWeek': None, >> u'timestamp_weekend': None, >> >> u'P0': { 'clipInput': True, >> ' fieldname': u'P0', >> 'maxval': 100.0, >> 'minval': 0.0, >> 'n': 50, >> 'name': u'P0', >> 'type': 'ScalarEncoder', >> 'w': 21 >> } >> u'P1': {} >> >> } >> >> >> >> _______________________________________________ >> nupic mailing list >> [email protected] >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org >> > > > > _______________________________________________ > nupic mailing > [email protected]http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > > > > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org > >
_______________________________________________ nupic mailing list [email protected] http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
