Description Usage Arguments Details Value
This algorithm finds the smallest positive root of a polynomial of second degree in λ. Bisection is an implicit algorithm, i.e., it calls itself until a certain precision is reached.
1 2 3 4 5 6 7 8 9  seagull_bisection(
ROWS,
ALPHA,
LEFT_BORDER,
RIGHT_BORDER,
GROUP_WEIGHT,
VECTOR_WEIGHTS,
VECTOR_IN
)

ROWS 
the length of the input vectors. 
ALPHA 
mixing parameter of the penalty terms. Satisfies: 0 < α < 1. The penalty term looks as follows: α * "lasso penalty" + (1α) * "group lasso penalty". 
LEFT_BORDER 
value of the left border of the current interval that for sure harbors a root. 
RIGHT_BORDER 
value of the right border of the current interval that for sure harbors a root. 
GROUP_WEIGHT 
a multiplicative scalar which is part of the polynomial. 
VECTOR_WEIGHTS 
an input vector of multiplicative scalars which are part of the polynomial. This vector is a subset of the vector of weights for features. 
VECTOR_IN 
another input vector which is required to compute the value of the polynomial. 
The polynomial has the following form:
∑_j (vector_j  α weight_j λ )^2_+  (1  α)^2 weight^2 λ^2.
The polynomial is nontrivial, because summands are part of the sum if and only if the terms are nonnegative.
If a certain precision (TOLERANCE
) is reached, this algorithm
returns the center point of the current interval, in which the root is
located. Otherwise, the function calls itself using half of the initial
interval, in which the root is surely located.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.