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Show HN: Unplugg: An automated Forecasting API for timeseries data

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Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#21

Post by ramblenode »

mgontav wrote: post #11
syntaxing wrote: post #10

I see from the earlier comments that this runs some sort of "optimized" ARIMA model. Is there anyway to output the statistical information of the fitted model though the API?

Not really. We're directing this more towards a completely automated use-case of forecasting with no human interaction, so it's not on our plans to release internal parameterization of the forecast.

IMO this would be much more appealing if there were an option to get the model details. I can't see myself presenting results to a group and answering the question "How did you get this?" with "Well, I put my data into this box and what came out seemed pretty good."

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#22

Post by mgontav »

ramblenode wrote: post #21
mgontav wrote: post #11

Earlier quoted context omitted.

Not really. We're directing this more towards a completely automated use-case of forecasting with no human interaction, so it's not on our plans to release internal parameterization of the forecast.

IMO this would be much more appealing if there were an option to get the model details. I can't see myself presenting results to a group and answering the question "How did you get this?" with "Well, I put my data into this box and what came out seemed pretty good."

Well, if we provide confidence intervals it should provide some kind of "safety"... but even so, with forecasting the only assurance you can get is by testing it against known historical values and checking it's accuracy (and even that way, historical results are no guarantee of future performance).

What kind of details would you say can be inspected to see if the model is reliable? AR or MA orders, inferred seasonalities? They can give me some notion of what kinds of assumptions were created about my data, but do not guarantee that it will perform :/

For instances where that kind of insight is needed, I don't think our way is the way to go, but rather the use of some forecasting package (R's Forecast or FB's Prophet) and a more exploratory work. But we're looking more at instances where what matters are the forecasted values and not so much the information underneath - automated anomaly detection systems, consumer-facing apps, and along those lines.

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#23

Post by tommynicholas »

mgontav wrote: post #19
GistNoesis wrote: post #18

Is this somehow connected to facebook Prophet? How do you compare?

We've been expecting this question all day long. As fate has it, we have no connection to FB's Prophet - we at Whitesmith have been working on unplugg for some time now and decided a few weeks ago that this week we'd share it on some communities to have more people testing it and more feedback. It seems that the folks over at Facebook decided something similar. You know what they say, great minds :p Joking aside, as…

Such a weird coincidence, but I definitely think you're in a different space. For example, per my previous comment where I needed it to be installed and more customizable, I'm going to use Prophet, but for other projects where it's not as important if Unplugg works I may use that.

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#24

Post by ashnyc »

@mgonatav . we are building an internal ERP for our manufacturing business. We use our sales data to try and predict what our future sales will look like. We try and produce what we think we are going to be selling in the next few months. Right, if we sale 3 items a day we just do a straight math and assume we will sale 3x10 in 10 days . I would like to talk to you and see how your service can help us

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#25

Post by mgontav »

ashnyc wrote: post #24

@mgonatav . we are building an internal ERP for our manufacturing business. We use our sales data to try and predict what our future sales will look like. We try and produce what we think we are going to be selling in the next few months. Right, if we sale 3 items a day we just do a straight math and assume we will sale 3x10 in 10 days . I would like to talk to you and see how your service can help us

Sure thing, shoot me an email at mgontav@unplu.gg and we'll see how we can help you out.

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#26

Post by ashnyc »

mgontav wrote: post #25
ashnyc wrote: post #24

@mgonatav . we are building an internal ERP for our manufacturing business. We use our sales data to try and predict what our future sales will look like. We try and produce what we think we are going to be selling in the next few months. Right, if we sale 3 items a day we just do a straight math and assume we will sale 3x10 in 10 days . I would like to talk to you and see how your service can help us

Sure thing, shoot me an email at mgontav@unplu.gg and we'll see how we can help you out.

Sent you an email. Thanks

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#27

Post by watty »

keredson wrote: post #12

{ "timestamp": 1458000000, "value": 63.422235 }, dear lord, why? this reminds me of the old "xml binary format" joke: 0 0 1 0 0 1 0 0

I don't get the snark - what's the glaring problem with the format? I work with sensor data at my job and very rarely is it uniformly distributed so we use a similar format.

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#28

Post by ramblenode »

mgontav wrote: post #22
ramblenode wrote: post #21

Earlier quoted context omitted.

IMO this would be much more appealing if there were an option to get the model details. I can't see myself presenting results to a group and answering the question "How did you get this?" with "Well, I put my data into this box and what came out seemed pretty good."

Well, if we provide confidence intervals it should provide some kind of "safety"... but even so, with forecasting the only assurance you can get is by testing it against known historical values and checking it's accuracy (and even that way, historical results are no guarantee of future performance). What kind of details would you say can be inspected to see if the model is reliable? AR or MA orders, inferred seasonal…

That's a fair answer. Your target audience is interested in prediction rather than inferring parameters.

I do think the confidence intervals/prediction intervals should be accessible and should probably be adjustable (e.g. 99%, 95%, 80%).

Re: Show HN: Unplugg: An automated Forecasting API for timeseries data

#29

Post by NumberCruncher »

mgontav wrote: post #19
GistNoesis wrote: post #18

Is this somehow connected to facebook Prophet? How do you compare?

We've been expecting this question all day long. As fate has it, we have no connection to FB's Prophet - we at Whitesmith have been working on unplugg for some time now and decided a few weeks ago that this week we'd share it on some communities to have more people testing it and more feedback. It seems that the folks over at Facebook decided something similar. You know what they say, great minds :p Joking aside, as…

The last time a start up tried to sell us a plug and play generic forecasting SAAS they made the mistake wanting to impress us and showing us their backend code. It was the first time in my life seeing spark code but it took only 10 minutes to find the spot being responsible for uncontrolled overfitting making their product useless. Every time I open a black box analytic tool happens the same.
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