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1 parent 75d3f29 commit bf8c57fCopy full SHA for bf8c57f
doc/modules/sgd.rst
@@ -371,7 +371,7 @@ Different choices for :math:`L` entail different classifiers or regressors:
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:math:`L(y_i, f(x_i)) = \log(1 + \exp (-y_i f(x_i)))`.
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- Least-Squares: Linear regression (Ridge or Lasso depending on
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:math:`R`).
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- :math:`L(y_i, f(x_i)) = \frac{1}{2}(y_i - f(x_i)^2`.
+ :math:`L(y_i, f(x_i)) = \frac{1}{2}(y_i - f(x_i))^2`.
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- Huber: less sensitive to outliers than least-squares. It is equivalent to
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least squares when :math:`|y_i - f(x_i)| \leq \varepsilon`, and
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:math:`L(y_i, f(x_i)) = \varepsilon |y_i - f(x_i)| - \frac{1}{2}
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