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- W4385200211 abstract "Analyzing categorical data in machine learning generally requires a coding strategy. This problem is common to multivariate statistical techniques, and several approaches have been suggested in the literature. This article proposes a method for analyzing categorical variables with neural networks. Both a supervised and unsupervised approaches were considered, in which the variables can have high cardinality. Some simulated data applications illustrate the interest in the proposal." @default.
- W4385200211 created "2023-07-25" @default.
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- W4385200211 date "2023-01-01" @default.
- W4385200211 modified "2023-09-23" @default.
- W4385200211 title "Optimal Coding of High-Cardinality Categorical Data in Machine Learning" @default.
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- W4385200211 doi "https://doi.org/10.1007/978-3-031-30164-3_4" @default.
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