[TriPython] Prediction Model. Data Visualization.

[Francois Dion]

Without the images, it is a bit hard to see what you are trying to achieve.

If what you are trying to do is represent a confusion matrix with a semi
graphical output (i'm all for that), then have a look at Yellow Brick. The
confusion matrix is here:
http://www.scikit-yb.org/en/latest/api/classifier/confusion_matrix.html

They also have a few more visualizations for classification:
http://www.scikit-yb.org/en/latest/#classification-visualization

Seaborn has a heatmap, so that can be used for a CM too. Now, if it has to
be on the web, interactive, look at bokeh or plot.ly. I did a plotly
presentation at PYPTUG last month, some code and a lot more stuff can be
found here: https://github.com/fdion/pyptug_plotly

Francois


On Tue, Oct 10, 2017 at 3:53 PM, Art <artem.nesterenko at gmail.com> wrote:

>    Good afternoon!
>    I'm reaching out to you guys for a suggestion on the data visualization.
>    I'm wondering if anyone has an experience or an idea of visualizing the
>    volume of multiple model prediction targets.
>    Here is an example of a model with just 2 prediction targets I've
> recently
>    been working on:
>    1. This model provides 2 predictions: target_1 and target_2.**
>    2. I also know the actual result to compare against, so I could see the
>    model accuracy.**
>    3. I've built a confusion matrix to calculate true/false pos/neg (see
>    below). So, there are 4 values.
>    4. I chose donut**chart to visualize these values (see below).
>    [1]Inline image 2**
>
>    My question is what if the model provides more than 2 predictions? Our
>    next model has 7 targets, which is 49 pos and neg values as far as I
>    understand. And I think a**donut**graph is not going to work in this
>    case.**Maybe a bar graph or something else fits better.**
>
>    I'd appreciate any ideas or examples of visualizations that easy to look
>    at and understand.
>    I'm using d3/c3.js for data visualization.
>    Thank you!
>    Art Nestsiarenka
>    email: [2]artem.nesterenko at gmail.com
>
> References
>
>    Visible links
>    2. mailto:artem.nesterenko at gmail.com
>
> _______________________________________________
> TriZPUG mailing list
> TriZPUG at python.org
> https://mail.python.org/mailman/listinfo/trizpug
> http://tripython.org is the Triangle Python Users Group
>
>


-- 
about.me/francois.dion - www.pyptug.org - www.3DFutureTech.info - @f_dion
<http://twitter.com/f_dion>
-------------- next part --------------
   Without the images, it is a bit hard to see what you are trying to
   achieve.

   If what you are trying to do is represent a confusion matrix with a semi
   graphical output (i'm all for that), then have a look at Yellow Brick. The
   confusion matrix is here:
   [1]http://www.scikit-yb.org/en/latest/api/classifier/confusion_matrix.html

   They also have a few more visualizations for classification:
   [2]http://www.scikit-yb.org/en/latest/#classification-visualization

   Seaborn has a heatmap, so that can be used for a CM too. Now, if it has to
   be on the web, interactive, look at bokeh or [3]plot.ly. I did a plotly
   presentation at PYPTUG last month, some code and a lot more stuff can be
   found here: [4]https://github.com/fdion/pyptug_plotly

   Francois
   On Tue, Oct 10, 2017 at 3:53 PM, Art <[5]artem.nesterenko at gmail.com>
   wrote:

     ** **Good afternoon!
     ** **I'm reaching out to you guys for a suggestion on the data
     visualization.
     ** **I'm wondering if anyone has an experience or an idea of visualizing
     the
     ** **volume of multiple model prediction targets.
     ** **Here is an example of a model with just 2 prediction targets I've
     recently
     ** **been working on:
     ** **1. This model provides 2 predictions: target_1 and target_2.**
     ** **2. I also know the actual result to compare against, so I could see
     the
     ** **model accuracy.**
     ** **3. I've built a confusion matrix to calculate true/false pos/neg
     (see
     ** **below). So, there are 4 values.
     ** **4. I chose donut**chart to visualize these values (see below).
     ** **[1]Inline image 2**

     ** **My question is what if the model provides more than 2 predictions?
     Our
     ** **next model has 7 targets, which is 49 pos and neg values as far as
     I
     ** **understand. And I think a**donut**graph is not going to work in
     this
     ** **case.**Maybe a bar graph or something else fits better.**

     ** **I'd appreciate any ideas or examples of visualizations that easy to
     look
     ** **at and understand.
     ** **I'm using d3/c3.js for data visualization.
     ** **Thank you!
     ** **Art Nestsiarenka
     ** **email: [2][6]artem.nesterenko at gmail.com

     References

     ** **Visible links
     ** **2. mailto:[7]artem.nesterenko at gmail.com

     _______________________________________________
     TriZPUG mailing list
     [8]TriZPUG at python.org
     [9]https://mail.python.org/mailman/listinfo/trizpug
     [10]http://tripython.org is the Triangle Python Users Group

   --
   [11]about.me/francois.dion - [12]www.pyptug.org -
   [13]www.3DFutureTech.info - [14]@f_dion

References

   Visible links
   1. http://www.scikit-yb.org/en/latest/api/classifier/confusion_matrix.html
   2. http://www.scikit-yb.org/en/latest/#classification-visualization
   3. http://plot.ly/
   4. https://github.com/fdion/pyptug_plotly
   5. mailto:artem.nesterenko at gmail.com
   6. mailto:artem.nesterenko at gmail.com
   7. mailto:artem.nesterenko at gmail.com
   8. mailto:TriZPUG at python.org
   9. https://mail.python.org/mailman/listinfo/trizpug
  10. http://tripython.org/
  11. http://about.me/francois.dion
  12. http://www.pyptug.org/
  13. http://www.3dfuturetech.info/
  14. http://twitter.com/f_dion