Tag: model interpretability

Advanced Analytics | Machine Learning
Austin Cook 0
Monotonic Constraints with SAS

A monotonic relationship exists when a model’s output increases or stays constant in step with an increase in your model’s inputs. Relationships can be monotonically increasing or decreasing with the distinction based on which direction the input and output travel. A common example is in credit risk where you would expect someone’s risk score to increase with the amount of debt they have relative to their income.

Advanced Analytics | Analytics | Artificial Intelligence | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 3]

In parts one and two of this blog posting series, we introduced machine learning models and the complexity that comes along with their extraordinary predictive abilities. Following this, we defined interpretability within machine learning, made the case for why we need it, and where it applies. In part three of

Advanced Analytics | Analytics | Artificial Intelligence | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 2]

In part one of this blog posting series, we introduced machine learning models as a multifaceted and evolving topic. The complexity that gives extraordinary predictive abilities also makes these models challenging to understand. They generally don’t provide a clear explanation, and brands experimenting with machine learning are questioning whether they

Advanced Analytics | Analytics | Artificial Intelligence | Customer Intelligence | Data Visualization | Machine Learning
Suneel Grover 0
SAS Customer Intelligence 360: A look inside the black box of machine learning [Part 1]

As machine learning takes its place in numerous advances within the marketing ecosystem, the interpretability of these modernized algorithmic approaches grows in importance. According to my SAS peer Ilknur Kaynar Kabul: We are surrounded with applications powered by machine learning, and we’re personally affected by the decisions made by machines

Advanced Analytics | Artificial Intelligence | Machine Learning
Ilknur Kaynar Kabul 0
Interpret model predictions with partial dependence and individual conditional expectation plots

We have updated our software for improved interpretability since this post was written. For the latest on this topic, read our new series on model-agnostic interpretability.  Assessing a model`s accuracy usually is not enough for a data scientist who wants to know more about how a model is working. Often

Advanced Analytics | Artificial Intelligence | Machine Learning
Ilknur Kaynar Kabul 0
Interpretability is crucial for trusting AI and machine learning

We have updated our software for improved interpretability since this post was written. For the latest on this topic, read our new series on model-agnostic interpretability.  As machine learning takes its place in many recent advances in science and technology, the interpretability of machine learning models grows in importance. We