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# frozen_string_literal: true
require 'rumale/base/base_estimator'
require 'rumale/base/transformer'
module Rumale
module Preprocessing
# Binarize samples according to a threshold
#
# @example
# binarizer = Rumale::Preprocessing::Binarizer.new
# x = Numo::DFloat[[-1.2, 3.2], [2.4, -0.5], [4.5, 0.8]]
# b = binarizer.transform(x)
# p b
#
# # Numo::DFloat#shape=[3, 2]
# # [[0, 1],
# # [1, 0],
# # [1, 1]]
class Binarizer
include Base::BaseEstimator
include Base::Transformer
# Create a new transformer for binarization.
# @param threshold [Float] The threshold value for binarization.
def initialize(threshold: 0.0)
check_params_numeric(threshold: threshold)
@params = { threshold: threshold }
end
# This method does nothing and returns the object itself.
# For compatibility with other transformer, this method exists.
#
# @overload fit() -> Binarizer
#
# @return [Binarizer]
def fit(_x = nil, _y = nil)
self
end
# Binarize each sample.
#
# @param x [Numo::DFloat] (shape: [n_samples, n_features]) The samples to be binarized.
# @return [Numo::DFloat] The binarized samples.
def transform(x)
x = check_convert_sample_array(x)
x.class.cast(x.gt(@params[:threshold]))
end
# The output of this method is the same as that of the transform method.
# For compatibility with other transformer, this method exists.
#
# @param x [Numo::DFloat] (shape: [n_samples, n_features]) The samples to be binarized.
# @return [Numo::DFloat] The binarized samples.
def fit_transform(x, _y = nil)
fit(x).transform(x)
end
end
end
end
Version data entries
16 entries across 16 versions & 1 rubygems