SAP HANA Predictive Analysis Library (PAL)

3.6.2 Binning Assignment
Binning assignment is used to assign data to the bins previously generated by the Binning algorithm.
Therefore it accepts a binning model as input.
It is assumed that the binning model generated in the previous binning stage includes bin starts (S) and ends
(E) of all bins, and therefore new data (d) can be assigned to bin i directly satisfying S i ≤ d < E i (for the last
bin, the less than relation should be less than or equal to).
There is some probability that new data locates too far away from all bins. Here the IQR technique is adopted
to justify if a piece of data is an outlier. If new data is lower than both Q1 – 1.5*IQR and the first bin start, or
higher than both Q3 + 1.5*IQR and the last bin end, it is regarded an outlier and assigned to a virtual bin of
index -1 without smoothing.
The new data will not update the binning model.
Note that for the cast of Equal Number Per Bin strategy, the new data assignment may violate its original
binning properties.
Prerequisites
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No missing or null data in the inputs.
Data types must be identical to those in the binning procedure.
The data types of the ID columns in the data input table and the result output table must be identical.
BINNINGASSIGNMENT
This function directly assigns data to bins based on the previous binning model, without running binning
procedure thoroughly.
Procedure Generation
CALL SYS.AFLLANG_WRAPPER_PROCEDURE_CREATE (‘AFLPAL’, ‘BINNINGASSIGNMENT’,
‘’, '', );
The signature table should contain the following records:
Table 313:
Position Schema Name Table Type Name Parameter Type
1
IN
2
IN
SAP HANA Predictive Analysis Library (PAL)
PAL Functions P U B L I C 437