For questions related to the "black box" nature of certain kinds of machine learning, where the internal decision making process is unknown.
Questions tagged [black-box]
5 questions
3
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1 answer
What exactly is an interpretable machine learning model?
From this page in Interpretable-ml book and this article on Analytics Vidhya, it means to know what has happened inside an ML model to arrive at the result/prediction/conclusion.
In linear regression, new data will be multiplied with weights and…
Naveen Reddy Marthala
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2
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1 answer
Black Box Explanations: Using LIME and SHAP in python
Recently, I came across the paper Robust and Stable Black Box Explanations, which discusses a nice framework for global model-agnostic explanations.
I was thinking to recreate the experiments performed in the paper, but, unfortunately, the authors…
user294142
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1
vote
1 answer
Optimizing a blackbox function with binary states
I have a non-linear black box function, which inputs a vector(size=250) and outputs a scalar value; f(x) = value.
The x variable is a vector of size 250 and has binary elements, e.g.: x = [0, 1, 1, 1, 0, 0, ...]
The result is just a scalar value…
oakca
- 111
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1
vote
0 answers
Alternatives to Bayesian optimization
I am given a dataset $\mathcal{D} = \{\mathbf{x}_i\}_{i=1}^n$ and I need to find the point (in my case a material) $\mathbf{x}^*$ that maximizes a property $y$ (which can be obtained from a black-box function $f(\mathbf{x}$), performing the least…
ado sar
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1 answer
What exactly is the AI explainability problem?
I am pretty new to AI and have recently been paying attention to AI explainability and the fact that it remains a hurdle within the path of commercializing certain AI systems in health for instance. I tried to do some digging myself by starting with…
rp2001
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