Optimization - Product Recommendation 1.0.2
This document summarizes major improvements and fixes introduced in the Accelerate Product Recommendation Optimization package release version.
Version | 1.0.2 |
|---|---|
Release Date | Jul 18, 2023 |
New Features and Improvements
Description | ID |
|---|---|
Python engine is now automatically deployed to the partition (if not already present) together with the accelerator. | PFPCS-6938 |
Fixed Issues
Bug Description | ID |
|---|---|
Product Recommendation step fails when Pricing Date is used for Basket ID but this field is not unique for each product-customer pair. To fix this issue, this corner case was implemented: transaction date is used for Basket ID and a customer orders the same product multiple times on a single date. | PFPCS-6808 |
The Product Recommendations step fails with an error "Input X contains NaN. AgglomerativeClustering does not accept missing values encoded as NaN natively..." This happens when the selected data only contains a single customer and model generated segments are selected. To fix this issue, recommendations for a single customer are now produced. | PFPCS-6811 |
When using model generated customer segments, you can get an error "cannot extract more clusters than samples". | PFPCS-6824 |
Product Recommendation's SegmentMapTable DMT fields are not classified (dimension vs. measure) and thus cannot be used by the Data Table input. | PFPCS-6831 |
The Product Recommendation step fails with an error "duplicate key value". | PFPCS-6862 |
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