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Submission GuidelinesHello,
After used the new "Image Recognition Tool" a few days, I think you could improve it :
> by adding the dimensional constraints in front of each of the pre-trained models,
> by adding a true tool to divide the training data correctly (in order to have an equivalent number of images for each of the labels)
> at least, allow the tool to use black & white images (I wanted to test it on the MNIST, but the tool tells me that it necessarily needs RGB images) ?
Question : do you in the future allow the user to choose between CPU or GPU usage ?
In any case, thank you again for this new tool, it is certainly perfectible, but very simple to use, and I sincerely think that it will allow a greater number of people to understand the many use cases made possible thanks to image recognition.
Thank you again
Kévin VANCAPPEL (France ;-))
Thank you again.
Kévin VANCAPPEL
It would be great if you could select multiple Data Fields in a single Crosstab
For example. I would like to SUM (Methodology) Pet Food Sales (Data Field 1) & Baby Food Sales (Data Field 2) By Store (Grouping Field) By Day of Week (Header field).
It would be great if there was an option to delete an expected column from a select tool. Sometimes I have to do a lot of work to rename different columns and would love to be able to copy & paste a select tool to partner with a slightly different input file. It would be great to delete an expected column, so I would not be forced to unselect the column to prevent error (I'd rather have the column treated as an *unknown) and I could use the remaining columns which are still applicable.
With a module that contains a lot of tool containers, it would be nice to have an option (similar to Disable All Tool That Write Output in the RunTime TAB) to disable all Tool Containers and then I can go pick the one or two that I would like to enable.
I have been using the outputs from Spline Regression to facillitate analysis of demographic data (specifically Department of Labor Quarterly Employment data). I have data from 1992Q1 to 2014Q1 and use Spline Regression to get fitted values for each quarter with predictors being the year/quarter, Year/quarter multiplied by a dummy variable for each of the 4 US Presidents, and a dummy variable for each president.
So I can compare results across various groupings by geographic, and other levels as well as the BLS aggregation level. I can analyze raw data or have the values to be fitted indexed to 1992Q1.
I use the default settings for Spline and it builds the best fit including where the node periods for each spline section. To help interpret the results, though, I use the output to compare the actual vs. fitted values (e.g. employment Level) and then look at the changes by quarter.
With the spline regression building the best model with optimal line segments, the results make it possible to see how employment progress or regress correletat with with presidential terms of office or specific impacts of economic recessions on employment data.
I can supply an example of the process, if anyone is interested.
I'd appreciate any comments and/or suggestions to improve the process or interpret the results.
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