feature selection
547 papers with code • 0 benchmarks • 1 datasets
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Distributed and parallel time series feature extraction for industrial big data applications
This problem is especially hard to solve for time series classification and regression in industrial applications such as predictive maintenance or production line optimization, for which each label or regression target is associated with several time series and meta-information simultaneously.
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
We introduce instancewise feature selection as a methodology for model interpretation.
Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets
However, the results have shown that the feature selection procedure used to create the comprehensive metafeatures is is not effective, since there is no gain in predictive performance.
A Debiased MDI Feature Importance Measure for Random Forests
Based on the original definition of MDI by Breiman et al. for a single tree, we derive a tight non-asymptotic bound on the expected bias of MDI importance of noisy features, showing that deep trees have higher (expected) feature selection bias than shallow ones.
Fair Kernel Regression via Fair Feature Embedding in Kernel Space
In this paper, we propose a new fair kernel regression method via fair feature embedding (FKR-F$^2$E) in kernel space.
Sequential Feature Classification in the Context of Redundancies
The problem of all-relevant feature selection is concerned with finding a relevant feature set with preserved redundancies.
Parametric Programming Approach for More Powerful and General Lasso Selective Inference
Unfortunately, the main limitation of the original SI approach for Lasso is that the inference is conducted not only conditional on the selected features but also on their signs -- this leads to loss of power because of over-conditioning.
VEST: Automatic Feature Engineering for Forecasting
Time series forecasting is a challenging task with applications in a wide range of domains.
Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
jnhwkim/orthoad
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We present the efficiency of semi-orthogonal embedding for unsupervised anomaly segmentation.
FaPN: Feature-aligned Pyramid Network for Dense Image Prediction
Recent advancements in deep neural networks have made remarkable leap-forwards in dense image prediction.
