Showing 2 open source projects for "input-output model"

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    Interpretable machine learning

    Interpretable machine learning

    Book about interpretable machine learning

    ...Machine learning is being built into many products and processes of our daily lives, yet decisions made by machines don't automatically come with an explanation. An explanation increases the trust in the decision and in the machine learning model. As the programmer of an algorithm you want to know whether you can trust the learned model. Did it learn generalizable features? Or are there some odd artifacts in the training data which the algorithm picked up? This book will give an overview over techniques that can be used to make black boxes as transparent as possible and explain decisions. ...
    Downloads: 1 This Week
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    simplex with branch and bound

    A tool for teaching simplex and branch & bound methods

    This is a tool for teaching simplex and branch & bound methods. For simplex method, it comes with several examples including degeneracy and cycling, and allow the user to dictate how to pivot. For branch and bound method, it is desinged to interact with the user to explore all possible branch and bound trees. The user can also load a problem from a text file or simply type in a model directly. The format is very simple and very similar to the LP format, see the packed-in examples.
    Downloads: 0 This Week
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