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Awesome GitHub RepositoriesCategorical Value Encoding
Using descriptive text labels and standard markers for categorical and missing data to prevent interpretation errors.
Distinct from Cardinality-Based Text Encoders: Existing candidates focus on neural encoders or binary-to-text encoding, not human-readable categorical labels for research data.
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- jtleek/datasharing
jtleek/datasharing
6,737Auf GitHub ansehenThis project is a research data sharing framework and provenance protocol designed to ensure computational reproducibility. It provides a standardized set of guidelines for transforming raw source data into tidy formats through documented processing scripts and cleaning workflows. The framework distinguishes itself by emphasizing a strict provenance-based packaging system. It requires the organization of raw data, processing recipes, and code books into a single package, ensuring that original unmodified sources are preserved to allow for independent verification of all transformation steps.
Implements standardized text-based encoding for categorical and missing values to prevent data interpretation errors.
