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Predictions in Kogito: PMML endpoints with OpenAPI

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Introduction PMML is an XML standard whose scope is to define different kinds of predictive models (Regression, Scorecard, Tree, Neural Network, etc) in a system-agnostic way, so that it may be used and shared by different systems/implementations. The OpenAPI Specification (OAS) defines a standard, language-agnostic interface to RESTful APIs which allows both humans and computersRead more →

Finding counterfactuals with OptaPlanner

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Modern enterprises are increasingly integrated with Machine Learning (ML) algorithms in their business workflows as a means of leveraging existing data, optimising decision making processes, detecting anomalies or simply reducing repetitive tasks. One of the challenges with ML methods, especially with internally complex predictive models, is being able to provide non-technical explanations on why aRead more →

Autotuning LIME explanations with few predictions

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Tuning algorithms, especially when machine learning is involved is often a tricky business. In this post we present an optimization based technique to automatically tune LIME in order to obtain more stable explanations. LIME (aka Local Interpretable Model agnostic explanations) is one of the most commonly used algorithms for generating explanations for AI based models.Read more →