Can you explain me how are calculated the SLA made by Thruk reporting module ?
I use it to provide KPIs to my customer and he ask me the calculation rules.
Thanks by advance.
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As part of our research we're conducted Controlled Interrupted Time Series Analysis on 35 individual case studies. In 33 instances the intervention occurs in isolation and can be analysed along standard lines. However, in 2 cases the intervention occurs alongside additional policy measures [that we do not have the data to replicate]. I had looked into methods, which suggested that one could account for coincident policies using an additional dummy variable, but am not sure I feel comfortable about such or really understand how to do so.
Just wondered if people had a view in regards to the above and could explain/point me in the direction of research that outlines the technical elements in regards to code or the mathematical formulation?
Any help hugely appreciated.
Cheers
Is it possible to decompose in details how much an additional line of code will impact the gas price for execution, i.e. transferring a token from one wallet to another, before deploying a smart contract?
Test networks are not very accurate there…
I think not. The final gas price is a dynamic variable. It depends on many other dynamic variables that cannot be computed beforehand because the actions these variables encode will happen in the future. Of course you can get an approximation based on the current gas price.
Is it possible to decompose in details how much an additional line of code will impact the gas price for execution, i.e. transferring a token from one
wallet to another, before deploying a smart contract?
Yes.
You can disassemble the compiled bytecode and then calculate the gas manually from the EVM instructions based on the Ethereum yellow paper.
I am trying to use collaborative filtering to recommend items to the user based on their past purchase. I have created a user vector representing his usage and item vector(A) with values populated as probabilty of B given A. The objective to somewhat capture the items sold together in items vector representation. Now I need to find the time when these recommendations should be presented. As the items I am recommending are of periodic use timing is very important.
So I am trying to explore constraint-based Recommendations to make my recommendation time sensitive. The approach I am thinking is to create time-sensitive constraint based on the last date of purchase and average consumption rate. But the problem is creating constraint as user level will become computationally difficult.
I need your suggestion regarding the approach or suggestion of any better way to implement the same. All I want to develop a recommendation engine using customer's usage data of items that are consumed and required to purchase again. I need to output list of recommendation as well as timing of presenting the recommendation to the user
Thanks
The way I see it, there are two basic options here that you can pursue. On the one hand, the temporal features can be incorporated as additional information and converted into a kind of hybrid recommendation. The Python package "lightfm" is a good example.
On the other hand, the problem can also be modeled as a time series problem. A well-known paper dealing with Next Basket Recommendations is "A Dynamic Recurrent Model for Next Basket Recommendation". Here too, there are already implementations on Github.
I have the following spreadsheet:
Cost Analysis Google Sheet
I am trying to think of the best way to analyze the cost impact on a Variant based on the different components of the product. I am having a very tough time trying to be creative and think of ways to identify cost trade-off analysis using Google Sheets.
Basically, I am trying to find methods within Sheets to help me visualize the added value of certain components for a Variant.
I know that this is difficult to do without any domain knowledge of the application, but I am hoping that someone has some more general ideas for how to do some reporting and visualization of data like this!
Thanks so much!
You have already added conditional formating, which I consider great for visual identification of tables, given that I don't think this model would be improved by a graph. First I would recommend changing the conditional formatting to gradual and having the green extreme be the maximum negative value of the Diff.-columns. Second, if you want the simplest visualization possible, you can do a rank-list.
This would work like a dashboard, presenting the variants with the information you want. Here is an example, which takes the PN-column of the row with the lowest Diff-value in the Variant 3-rows: =index(G3:I16,match(vlookup(SMALL(I3:I16,1),I3:I16,1,false),I3:I16),1)
You can then alter the rank and the offset, to get a list for the # best variants with the columns you want.
Hope that helps, for the visualization. For advice on organization, I believe Google Sheets-forum is less appropriate :)
the customer I'm working for uses JIRA. However since they have a big Enterprise license (~2k users) they will not sign off additional plugins that would only be used by a comparatively small amount of users.
However, we in lead development have to present a few figures that we have to assemble manually at the moment. We are supposed to be able to always tell for one release how many hours are already "booked". (Original) Estimates are added reliably to all issues and everything is assigned to exactly one release. Based on the amount of workers in the team I can calculate the number of hours we have for the next release.
Is there any built-in possibility to do a report for this at any time? I'm a bit lost at the moment since I wonder where I'd store or how I'd calculate the amount of hours.
Note: we're not allowed to buy plugins, but we have coders at our fingertips. :D So a hint on how to script or code this would be appreciated as well.
Thanks a lot!
I think that the easiest approach is to use JIRA REST API to extract the info you need. So this is task for your coders :-).
Please take a look on search method: https://docs.atlassian.com/jira/REST/latest/#d2e2450
I think that you can start with request like
/rest/api/2/search?jql=fixVersion=YOUR_RELEASE