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Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network
Missing data is one of the most common preprocessing problems.
Unsupervised Latent Space Translation Network
One task that is often discussed in a computer vision is the mapping of an image from one domain to a corresponding image in another domain known as image-to-image translation.
Missing Features Reconstruction and Its Impact on Classification Accuracy
The imputation impact is researched on a combination of traditional methods such as k-NN, linear regression, and MICE compared to modern imputation methods such as multi-layer perceptron (MLP) and gradient boosted trees (XGBT).
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