How can I find out what features the total score returned from products is based on on Solr? - search

How can I find out what features the total score returned from products is based on on Solr? I'll print these scores one by one elsewhere.
I want to see what the total scores of the products returned from Solr are based on.


Power Bi - Competitor Average Price Measure

Attached is the data I have the question for. I want to create a Measure in Power Bi that gives me the average price of a competitor's farm product. (If looking at Beth's product I want to see the average of Amy's product) If a filter is applied (Example: Product type = Fruit) then I want to see the average price of Amy's fruits). The goal of this is to find the % difference each product is from its filtered competition.
SpreadSheet Data
My unsuccessful attempt:

how to create a score based (or ranking based) column on excel?

my database
What I want to achieve: Find the city where my tv ads have the best performance (high volume of signups at a lower cost).
What I am doing: In order to see the best combination of the metrics, I attributed a score for each metric column. Then, I sum all the scores (column M). The highest score is the city with the best performance.
What I would like to do: To automate the score columns. Is the a way to make those scores with formulas or code? (the score goes from 1 to [number of lines]). Also, I'd love to know if theres a better way to make this correlation.
If it's a regular table, you can use RANK().
So, add a column like "rank" to your table.
and put this into the first row under "rank":
=RANK([#[Total Score]];[Total Score];0)
It basically takes the total score of the current row, and checks it's ranking in the whole "total score"-column. The zero is to give the highest value the lowest rank.
Have fun! ^_^

Fleiss-kappa score for interannotator agreement

In my dataset I have a set of categories, where for every category I have a set of 150 examples. Each example has been annotated as true/false by 5 human raters. I am computing the inter-annotator agreement using the Fleiss-kappa score:
1) for the entire dataset
2) for each category in particular
However, the results I obtained show that the Fleiss-kappa score for the entire dataset does not equal the average of the Fleiss-kappa score for each category. In my computation I am using a standard built-in package to compute the scores. Could this be due to a bug in my matrix computation, or are the scores not supposed to be equal? Thanks!

How to get max value or last value for default rating setting column in SharePoint 2013

I want latest rating count value for default ratting setting column instead of average count. How can
i achieve this by using out of box settings or by customization..? Thanks in advance.
I want Rating Value(0-5) of last user who rated the specific document/Image instead of average rating value.
Number of Ratings provide the count for users who had rated the document..
when you enable ratings on any list or library, the two Site Columns that gets added to the SharePoint list are:
Rating - which provides the average rating
Number of Ratings- Which provides the rating count.
Number of ratings field will provide the latest count value

finding the closest match based on multiple criteria

Ive been working on VBA at work for almost a year and have managed to pull of some rather impressive things, normally I can find anything I'm not sure about with a series of searches on this site or others but this time I have come up blank, I guess its most likely because I don't really know how to frame the search properly :(
I'm looking to create a macro that analyses a customers sales history, then preforms a 'you might also like' search from our bestsellers list and returns the closest match to their bestseller. The product is books and due to many decades of bibliographic attention to detail within the industry each product can have up to 20 categories and I want to use this to find the closet match.
The info I have (the important bits)
Sheet 1 - product id - customer sales quantity
Product id 2 -customer sales quantity
Product id 3 -customer sales quantity
Etc etc ( usually up to 100)
Sheet 2 - product id - total company sales quantity
product id2 - total company sales quantity product id3 - total company sales quantity
Etc etc (Currently over 34000 and growing...)
Sheet 3 - cat1 cat2 cat3 cat4 cat5 cat6 etc (to cat400)
Product id 1 0 1 1 0 0
Product id2 0 1 1 0 1 0
Product id3 1 0 1 1 0 0
What I want to be able to is to find the bestseller from the customers list, look up all of the matching categories for that product on the cat reference table, find all results with an exact match to those categories and list them by total company's sales value. Although it is very possible that with the amount of possible categories there will not be an exact mach so I would like then to get the closest match of that product.....
Does that make sense? Please let me know if any more info is needed to help - even just a pointer towards some kind of function or a snippet of code that will help me on my way would be appreciated, I just have no idea how to find a match for an entire rows values.... and even less of an idea of how to find a closest match if there are no exacts...
Interesting question. There's no match function to achieve what you want. Instead, you need to first figure out what kind of algorithm/logic you want to use in order to determine the closest books. This will require a lot of weighing. Here's how I'd do it (without VBA):
Let's use the following data as example:
Combine product info with overall sales info, to have a weight for each book:
Determine to the "average preference" of the customers basket in sheet1. In order to do so:
Add the category information for the 400 categories to each product in the basket:
Sum each category for all basket products (see row 6 above)
Determine the weigh (see row 7).
Apply this preference to all products to determine the overall fit:
Compare each product's categories with the preference:
Check that the product is not already in the basket:
Combine all three factor to determine each product's fit (by multiplying the factors) - and rank them using the RANK function:
Last but not least, retrieve the top X highest matches with a lookup:
Here's the sample file.