CPC G06F 11/3452 (2013.01) [G06F 11/3428 (2013.01); G06N 20/00 (2019.01)] | 20 Claims |
1. A computer-implemented method comprising:
assessing a performance of a plurality of unsupervised machine learning pipelines against a plurality of data sets;
associating the performance with meta-features corresponding to respective pipeline/data set combinations;
training a supervised meta-learning model using the associated performance and meta-features as training data; and
utilizing the trained model to identify one or more pipelines for processing an input data set.
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