Overview of Binning Explorer
The Binning Explorer app enables you to interactively bin credit scorecard data. Use the Binning Explorer to:
Select an automatic binning algorithm with an option to bin missing data. (For more information on algorithms for automatic binning, see
autobinning
.)Shift bin boundaries.
Split bins.
Merge bins.
Save and export a
creditscorecard
object.
Binning Explorer complements the overall workflow for developing a credit scorecard
model. Use screenpredictors
to pare
down a potentially large set of predictors to a subset that is most predictive of the
credit score card response variable. You can then use this subset of predictors when
using Binning Explorer to create the creditscorecard
object.
Using Binning Explorer: | |
---|---|
1. | Open the Binning Explorer app.
|
2. | Import the data into the app. You can import
data into Binning Explorer by either starting directly
from a data set or by loading an existing |
3. | Use Binning Explorer to work interactively with the binning assignments for a scorecard. |
4. | Export the scorecard to a new Continue
the workflow from the MATLAB command line using |
Using creditscorecard Object
Functions in Financial Toolbox: | |
5. | Fit a logistic regression model. |
6. | Review and format the credit scorecard points. |
7. | Score the data. |
8. | Calculate the probabilities of default for the data. |
9. | Validate the quality of the credit scorecard model. |
For more detailed information on this workflow, see Bin Data to Create Credit Scorecards Using Binning Explorer.
See Also
Apps
Classes
Related Examples
- Common Binning Explorer Tasks
- Bin Data to Create Credit Scorecards Using Binning Explorer
- Case Study for Credit Scorecard Analysis