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[python-package] [docs] Expand class docs for Dataset (#6558)
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@ -63,4 +63,4 @@ Imports:
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utils
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SystemRequirements:
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~~CXXSTD~~
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RoxygenNote: 7.3.1
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RoxygenNote: 7.3.2
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@ -758,8 +758,13 @@ Dataset <- R6::R6Class(
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)
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#' @title Construct \code{lgb.Dataset} object
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#' @description Construct \code{lgb.Dataset} object from dense matrix, sparse matrix
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#' or local file (that was created previously by saving an \code{lgb.Dataset}).
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#' @description LightGBM does not train on raw data.
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#' It discretizes continuous features into histogram bins, tries to
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#' combine categorical features, and automatically handles missing and
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# infinite values.
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#'
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#' The \code{Dataset} class handles that preprocessing, and holds that
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#' alternative representation of the input data.
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#' @inheritParams lgb_shared_dataset_params
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#' @param data a \code{matrix} object, a \code{dgCMatrix} object,
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#' a character representing a path to a text file (CSV, TSV, or LibSVM),
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@ -60,8 +60,12 @@ second group, etc.}
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constructed dataset
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}
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\description{
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Construct \code{lgb.Dataset} object from dense matrix, sparse matrix
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or local file (that was created previously by saving an \code{lgb.Dataset}).
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LightGBM does not train on raw data.
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It discretizes continuous features into histogram bins, tries to
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combine categorical features, and automatically handles missing and
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The \code{Dataset} class handles that preprocessing, and holds that
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alternative representation of the input data.
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}
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\examples{
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\donttest{
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@ -12,7 +12,7 @@ dependencies:
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- r-markdown=1.12
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- r-matrix=1.6_4
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- r-pkgdown=2.0.7
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- r-roxygen2=7.3.1
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- r-roxygen2=7.3.2
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- scikit-learn>=1.4.0
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- sphinx>=6.0
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- sphinx_rtd_theme>=2.0
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@ -1745,7 +1745,15 @@ class _InnerPredictor:
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class Dataset:
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"""Dataset in LightGBM."""
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"""
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Dataset in LightGBM.
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LightGBM does not train on raw data.
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It discretizes continuous features into histogram bins, tries to combine categorical features,
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and automatically handles missing and infinite values.
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This class handles that preprocessing, and holds that alternative representation of the input data.
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"""
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def __init__(
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self,
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