In JMP 12, an interactive HTML Profiler was added, as I had previously blogged about. That change mainly updated the existing Flash functionality to HTML5 technology, making it available on mobile devices like an iPad, but it also introduced a few new features. Among these was the option of exporting the Fit Model Least Squares platform report as a whole with an interactive Profiler embedded within it.
After users got to try this tool, the response was overwhelmingly positive. They found it a great way to explore cross-sections of predicted responses across multiple factors with other people who don’t have JMP yet. However, the feedback was that users would like to see Profilers available in other platforms as well.
In JMP 13, three more platforms have embedded Profilers that are available in interactive HTML.
In JMP, you can analyze your data using Neural Networks. I will use the Diabetes data set from the sample data library to illustrate some of the differences between this platform and Generalized Regression below. Note the curved responses for Age, BMI, and BP as well as the elongated report (only the first five factors out of 10 are shown).
Generalized Regression embedded Profilers are supported for export from JMP Pro 13. This example also shows an additional enhancement for Interactive HMTL in JMP 13 that allows you to pick how many plots are displayed in a row when you have a lot of factors. You'd do this in JMP by selecting the red triangle, going to Appearance and selecting Arrange in Rows to provide the number you want before exporting. This allows you to explore many factors in Interactive HTML with a nice layout (which can be useful on a mobile device with a smaller screen). You can see the same factors analyzed as in the Neural platform above, but more are visible in the same width display due to this feature.
Generalized Linear Model
Generalized Linear Model is the third platform to support interactive HTML embedded Profilers in JMP 13.
In addition to making embedded Profilers in those three platforms available in interactive HTML, JMP 13 includes new features to make exploring your data a little easier. That's what I'll cover in the following sections.
Adapt Y Axis
In JMP 12, you could explore data outside of the initial range of the numeric factors by typing in a value in the edit box below the curve. But what if this causes the curve to move outside the initial range of the response? You could see the value displayed in red on the Y axis, but no longer see the curve itself. Now there is an option to have the Y axis automatically adapt to show the min and max values of the curve. Simply click the menu button above the Profiler and check “Adapt Y Axis”.
Some data requires analyzing a formatted X factor such as a date, time, or geographic location. In JMP 12, you could click or drag anywhere within the Profiler to change the value, but there was no way to provide a precise value for this type of data. Now X variables in these formats are displayed as a button that, when clicked, launches a dialog to enter the individual fields of the format.
Similarly, in JMP 12, if you tried to precisely set a Profiler with a mixture constraint to a set of values that you knew satisfied the constraint, you couldn’t do it; every time you set one value, the others were altered to satisfy the mixture. In JMP 13, mixture values are applied by clicking an apply button.
For example, the amounts of three ingredients used to make a plastic in the following Profiler must sum to 1 and stay within the ranges shown. The values 0.7, 0.1, and 0.2 sum to 1 exactly. So, by entering these values in the edit boxes and then clicking apply, the Profiler is set to those precise values.
The images shown here as well as a few other examples are available as live interactive HTML files to explore on the web.
JMP offers a wide variety of math functions, special features and powerful algorithms that haven’t all been implemented in HTML, so not every Profiler will come out interactively. If you need to share work with someone who doesn’t have JMP and export your reports to Interactive HTML, we’ve added messages to the log to try to indicate why a particular Profiler has come out as a static image. Armed with this knowledge, we hope you will try your own Profilers and give us feedback on what features and platforms you want to see in the future.
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