measures

问题 I am adding distinct order count measure to the cube. I have to place it in a separate measure group for better performance When I click on "new measure group" button, I am presented with a dialog box "select a table from the source view" . My Facts_sales table is not on the list. because the table is already used by other measure group "Facts_sales". How could I create a new measure group for the distinct count measure? 回答1: Just create a new measure in the group referencing the fact table

问题 I have a repeated measures data set. I need to remove all Participants where the number of observations for that individual is less than 3. What is the best way to do this? x <- c(9, 9, 9, 11, 11, 23, 23, 23, 23, 45, 45, 45, 56, 56) Here 11 and 56 need to be removed from the data. So far I have created a data frame with all the obs that I want to keep but not sure how to manipulate my data set using the new data frame x <- as.data.frame(table(x)) x1 <- x[x$Freq > 2,] 回答1: x[x %in% names(table

问题 There is a Sales Invoice dimension which is related to Sales measures. Sales measures are partitioned. I have 2011 partition and 2012 partition. I figured that we don't need to process Sales 2011 partition because it doesn't change anymore. Unfortunately (confirmed by "impact analysis") after reprocessing of Sales Invoice dimension my both Sales Measure partitions become Unprocessed. Is there a way to avoid that? Please note that primary key doesn't change. Processing takes place in SSIS

问题 I want to know the possible measures that can be used to measure the accuracy of my image segmentation algorithm I know the following methods: sensitivity specificity Dice index Jaccard index But I am working with large data set that needs to be tested, So I think measuring accuracy with each pixel value will not be very suitable. So, I am looking for other more convenient measures. P.S: I have ground truth data 回答1: The question of "accuracy" in image segmentation is ill-defined, resulting