Weiru, Currently there is no way to swarm over CoordinateEncoder parameters. Swarming attempts to find the best parameters for *predicting* a certain input field, and currently we cannot make predictions with the CoordinateEncoder [1].
So currently you can only do anomaly detection with coordinates, which uses a pre-configured set of model params, so swarming is unnecessary. [1] http://lists.numenta.org/pipermail/nupic_lists.numenta.org/2015-July/011380.html Regards, --------- Matt Taylor OS Community Flag-Bearer Numenta On Mon, Nov 23, 2015 at 6:36 AM, Weiru Zeng <[email protected]> wrote: > Hello Kentaro: > > Thanks for your help, and the model_params.py help me great, but I still > want to know that how can I configure swarmming description file > search_def.json to make a coordinateEncoder. Becouse I think the model > generated by the swarming process will be more accurate. So are there some > friends who know how should I do? > > thanks everyone! > > > ------------------ 原始邮件 ------------------ > 发件人: "Kentaro Iizuka";<[email protected]>; > 发送时间: 2015年11月17日(星期二) 晚上10:29 > 收件人: "Weiru Zeng"<[email protected]>; > 主题: Re: Question about running swarming > > Hello Weiru, > > I tried to use your `13.csv` data with CoordinateEncoder. > Here is the sample code. > > https://gist.github.com/iizukak/885b11fc33db566c5e3d > > It’s not OPF, but I think you will find how to use CoordinateEncoder. > BTW, your CSV's first column looks incorrect. > > Thanks. > > 2015-11-17 20:16 GMT+09:00 Weiru Zeng <[email protected]>: >> thank you for your reply. >> >> I have some data which contain coordinate and the date is attached by this >> mail. I have searched almost all the documents, but can not find any >> information about how to edit the search_def.josn file to make the opf use >> the CoordianteEncoder to encode the input data. The fields I want to >> predict >> is the coordiante (x,y,z), the predictionSteps is 1. And how to edit the >> search_def.json file? >> >> Weiru Zeng >> >> >> ------------------ 原始邮件 ------------------ >> 发件人: "Matthew Taylor";<[email protected]>; >> 发送时间: 2015年11月17日(星期二) 上午6:48 >> 收件人: "Weiru Zeng"<[email protected]>; >> 主题: Re: Question about running swarming >> >> There are many reasons you may be getting a bad prediction. One major >> reason could be that the data is not predictable. >> >> By the way, you can run the exact experiment you're trying with a very >> simple Menorah script: >> https://gist.github.com/rhyolight/d9342c4f0ada961ee406 >> >> You just need to "pip install menorah" first. >> >> When I ran, I got the following from the swarm: >> >> Field Contributions: >> { u'chicago-beach-water-quality Calumet Beach turbidity': >> 13.665743305632503, >> u'chicago-beach-water-quality Calumet Beach water_temperature': >> 10.618651892890124, >> u'chicago-beach-water-quality Calumet Beach wave_height': >> 4.709141274238225, >> u'chicago-beach-water-quality Calumet Beach wave_period': >> 16.712834718374882, >> u'timestamp_dayOfWeek': 15.050784856879035, >> u'timestamp_timeOfDay': -11.04578340758864, >> u'timestamp_weekend': 0.0} >> >> These numbers are rather low, which tells us that wave_period may not >> be very predictable. >> >> --------- >> Matt Taylor >> OS Community Flag-Bearer >> Numenta >> >> >> On Tue, Nov 10, 2015 at 5:39 AM, Weiru Zeng <[email protected]> wrote: >>> Hi nupic: >>> >>> Recent I used the nupic to make prediction, and I attached my data and >>> the >>> .json file with this email. Run the swarming with my code and data, you >>> will find the low constribution of the field, and it makes a bad >>> prediction. >>> My question is below: >>> >>> First: Is the bad predicion caused by my .json file? >>> Second: The low contribution of all the fields means that the feature in >>> the >>> data is not enough to make a good prediction. Is that right? >>> Last: This is about the .json file. I found that there is a item named >>> "aggregation" in some other .json file, the detail is below: >>> >>> "aggregation": { >>> "hours": 1, >>> "microseconds": 0, >>> "seconds": 0, >>> "fields": [ >>> [ >>> "consumption", >>> "sum" >>> ], >>> [ >>> "gym", >>> "first" >>> ], >>> [ >>> "timestamp", >>> "first" >>> ] >>> ], >>> "weeks": 0, >>> "months": 0, >>> "minutes": 0, >>> "days": 0, >>> "milliseconds": 0, >>> "years": 0 >>> } >>> >>> I atempted to set it, but fieled. I want to know what's the means of the >>> time and the fields?. When should I set the time to 1, and how to set the >>> "fields"?. >>> >>> Thanks in advance! >>> >>> Weiru Zeng > > > > -- > Kentaro Iizuka<[email protected]> > > Github > https://github.com/iizukak/ > > Facebook > https://www.facebook.com/kentaroiizuka
