The polynomial features transformer maps a vector into the polynomial feature space of degree $d$. The dimension of the input vector determines the number of polynomial factors whose values are the respective vector entries. Given a vector $(x, y, z, \ldots)^T$ the resulting feature vector looks like:
Flinkās implementation orders the polynomials in decreasing order of their degree.
Given the vector $\left(3,2\right)^T$, the polynomial features vector of degree 3 would look like
This transformer can be prepended to all Transformer
and Predictor
implementations which expect an input of type LabeledVector
or any sub-type of Vector
.
PolynomialFeatures
is a Transformer
.
As such, it supports the fit
and transform
operation.
PolynomialFeatures is not trained on data and, thus, supports all types of input data.
PolynomialFeatures transforms all subtypes of Vector
and LabeledVector
into their respective types:
transform[T <: Vector]: DataSet[T] => DataSet[T]
transform: DataSet[LabeledVector] => DataSet[LabeledVector]
The polynomial features transformer can be controlled by the following parameters:
Parameters | Description |
---|---|
Degree |
The maximum polynomial degree. (Default value: 10) |