Additive models
57 papers with code • 0 benchmarks • 0 datasets
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Use these libraries to find Additive models models and implementationsMost implemented papers
Neural Additive Models: Interpretable Machine Learning with Neural Nets
They perform similarly to existing state-of-the-art generalized additive models in accuracy, but are more flexible because they are based on neural nets instead of boosted trees.
Augmenting Interpretable Models with LLMs during Training
csinva/imodelsX
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Recent large language models (LLMs) have demonstrated remarkable prediction performance for a growing array of tasks.
Additive Approximations in High Dimensional Nonparametric Regression via the SALSA
Between non-additive models which often have large variance and first order additive models which have large bias, there has been little work to exploit the trade-off in the middle via additive models of intermediate order.
Stability selection for component-wise gradient boosting in multiple dimensions
We apply this new algorithm to a study to estimate abundance of common eider in Massachusetts, USA, featuring excess zeros, overdispersion, non-linearity and spatio-temporal structures.
Do Not Trust Additive Explanations
Explainable Artificial Intelligence (XAI)has received a great deal of attention recently.
Semi-Structured Distributional Regression -- Extending Structured Additive Models by Arbitrary Deep Neural Networks and Data Modalities
We propose a general framework to combine structured regression models and deep neural networks into a unifying network architecture.
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions
The lack of interpretability is an inevitable problem when using neural network models in real applications.
How Interpretable and Trustworthy are GAMs?
Generalized additive models (GAMs) have become a leading modelclass for interpretable machine learning.
Fast Interpretable Greedy-Tree Sums (FIGS)
The total number of splits across all the trees can be restricted by a pre-specified threshold, thereby keeping both the size and number of its trees under control.
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
The number of information systems (IS) studies dealing with explainable artificial intelligence (XAI) is currently exploding as the field demands more transparency about the internal decision logic of machine learning (ML) models.
