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1. towardsdatascience.com › machine-learningBlack-box vs. white-box models. Most machine learning systems ...

   towardsdatascience.com › machine-learning

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   Mar 14, 2019 · They serve primarily as ‘global summary’ of a model. The following steps illustrate how you can build a surrogate model for any black-box model. Train a black-box model. Evaluate the black box model on the dataset. Choose an interpretable surrogate model (typically a linear model or a decision tree).

   • Author: Lars Hulstaert

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3. www.toolify.ai › ai-news › understanding-theUnderstanding the Differences Between Black Box and White Box ...

   www.toolify.ai › ai-news › understanding-the

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   In the world of machine learning and artificial intelligence, two terms frequently pop up: black box models and white box models. Each of these models has its own distinctive characteristics, advantages, and applications.

4. www.toolify.ai › gpts › understanding-white-box-andUnderstanding White Box and Black Box Models in Machine Learning

   www.toolify.ai › gpts › understanding-white-box-and

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   Dec 21, 2023 · Black box models and white box models refer to the level of interpretability and transparency within machine learning models. A black box model is a complex algorithmic model where the user does not have access to the internal workings or logic of the model.

5. ieeexplore.ieee.org › document › 8882211Black-Box vs. White-Box: Understanding Their Advantages and ...

   ieeexplore.ieee.org › document › 8882211

   Oct 24, 2019 · This paper shows that both approaches are suitable for solving practical problems, but experts in machine learning need to understand the input data, the problem to solve, and the best way for showing the output data before applying a machine learning model.

   • Author: Octavio Loyola-González

   • Publish Year: 2019

6. www.activestate.com › blog › white-box-vs-black-boxWhite Box vs. Black Box Algorithms in Machine Learning

   www.activestate.com › blog › white-box-vs-black-box

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   Jul 19, 2023 · What Is a Black Box Machine Learning Model and How Do You Build One? Black box machine learning models (Black Boxes), on the other hand, rank higher on innovation and accuracy, but lower on transparency and interpretability.

7. blog.dataiku.com › white-box-vs-black-box-modelsWhite Box vs Black Box Models: Finding the Balance - Dataiku

   blog.dataiku.com › white-box-vs-black-box-models

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   Jan 31, 2020 · White Box vs Black Box Models: Finding the Balance. Data scientists and business leaders building or using machine learning models and AI systems face a serious challenge today — how to balance interpretability and accuracy stemming from the difference between black-box and white-box models.

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   What is a black box machine learning model?

   • Black box machine learning models (Black Boxes), on the other hand, rank higher on innovation and accuracy, but lower on transparency and interpretability. Black Boxes produce output based on your input data set, but do not – and cannot – clarify how they came to those conclusions.

   White Box vs. Black Box Algorithms in Machine Learning - ActiveState

   www.activestate.com/blog/white-box-vs-black-box-algorithms-in-machine-learning/

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   What is the difference between a black box and a white box model?

   • On the other hand, white-box models have observable/understandable behaviors, features, and relationships between influencing variables and the output predictions (think: linear regressions and decision trees), but are often not as performant as black-box models (i.e, lower accuracy, but higher explainability).

   White Box vs Black Box Models: Finding the Balance - Dataiku

   blog.dataiku.com/white-box-vs-black-box-models-balancing-interpretability-and-accuracy

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   What is a white box machine learning model?

   • A white box machine learning model (White Box) is one that allows humans to easily interpret how it was able to produce its output and draw its conclusions, thereby giving us insight into the algorithm’s inner workings. White boxes are transparent in terms of: Examples of such models include linear trees, decision trees, and regression trees.

   White Box vs. Black Box Algorithms in Machine Learning - ActiveState

   www.activestate.com/blog/white-box-vs-black-box-algorithms-in-machine-learning/

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   What is a black box model?

   • Black Boxes tend to model extremely complex scenarios with deep and non-linear interactions between the data. Some examples include: It is typical for such models to apply high-dimensional and non-linear transformations to the input variables (which is already at a complexity beyond human understanding).

   White Box vs. Black Box Algorithms in Machine Learning - ActiveState

   www.activestate.com/blog/white-box-vs-black-box-algorithms-in-machine-learning/

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9. smitan94.github.io › Black-Box-vs-White-BoxWhite box vs Black Box models: Importance of interpretable ...

   smitan94.github.io › Black-Box-vs-White-Box

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   Sep 2, 2020 · White box vs Black Box models: Importance of interpretable model in today’s world - Smitan Pradhan. 5 minute read. INTRODUCTION: Machine Learning has come a long way in the last decade or so.