Generating Synthetic Data

X, y = make_blobs(n=100, p=2; kwargs...)

Generate Gaussian blobs for clustering and classification problems.

Return value

By default, a table X with p columns (features) and n rows (observations), together with a corresponding vector of n Multiclass target observations y, indicating blob membership.

Keyword arguments

• shuffle=true: whether to shuffle the resulting points,

• centers=3: either a number of centers or a c x p matrix with c pre-determined centers,

• cluster_std=1.0: the standard deviation(s) of each blob,

• center_box=(-10. => 10.): the limits of the p-dimensional cube within which the cluster centers are drawn if they are not provided,

• eltype=Float64: machine type of points (any subtype of AbstractFloat).

• rng=Random.GLOBAL_RNG: any AbstractRNG object, or integer to seed a MersenneTwister (for reproducibility).

• as_table=true: whether to return the points as a table (true) or a matrix (false). If false the target y has integer element type.

Example

X, y = make_blobs(100, 3; centers=2, cluster_std=[1.0, 3.0])

X, y = make_circles(n=100; kwargs...)

Generate n labeled points close to two concentric circles for classification and clustering models.

Return value

By default, a table X with 2 columns and n rows (observations), together with a corresponding vector of n Multiclass target observations y. The target is either 0 or 1, corresponding to membership to the smaller or larger circle, respectively.

Keyword arguments

• shuffle=true: whether to shuffle the resulting points,

• noise=0: standard deviation of the Gaussian noise added to the data,

• factor=0.8: ratio of the smaller radius over the larger one,

• eltype=Float64: machine type of points (any subtype of AbstractFloat).

• rng=Random.GLOBAL_RNG: any AbstractRNG object, or integer to seed a MersenneTwister (for reproducibility).

• as_table=true: whether to return the points as a table (true) or a matrix (false). If false the target y has integer element type.

Example

X, y = make_circles(100; noise=0.5, factor=0.3)

make_moons(n::Int=100; kwargs...)

Generates labeled two-dimensional points lying close to two interleaved semi-circles, for use with classification and clustering models.

Return value

By default, a table X with 2 columns and n rows (observations), together with a corresponding vector of n Multiclass target observations y. The target is either 0 or 1, corresponding to membership to the left or right semi-circle.

Keyword arguments

• shuffle=true: whether to shuffle the resulting points,

• noise=0.1: standard deviation of the Gaussian noise added to the data,

• xshift=1.0: horizontal translation of the second center with respect to the first one.

• yshift=0.3: vertical translation of the second center with respect to the first one.

• eltype=Float64: machine type of points (any subtype of AbstractFloat).

• rng=Random.GLOBAL_RNG: any AbstractRNG object, or integer to seed a MersenneTwister (for reproducibility).

• as_table=true: whether to return the points as a table (true) or a matrix (false). If false the target y has integer element type.

Example

X, y = make_moons(100; noise=0.5)

make_regression(n, p; kwargs...)

Generate Gaussian input features and a linear response with Gaussian noise, for use with regression models.

Return value

By default, a tuple (X, y) where table X has p columns and n rows (observations), together with a corresponding vector of n Continuous target observations y.

Keywords

• intercept=true: Whether to generate data from a model with intercept.

• n_targets=1: Number of columns in the target.

• sparse=0: Proportion of the generating weight vector that is sparse.

• noise=0.1: Standard deviation of the Gaussian noise added to the response (target).

• outliers=0: Proportion of the response vector to make as outliers by adding a random quantity with high variance. (Only applied if binary is false.)

• as_table=true: Whether X (and y, if n_targets > 1) should be a table or a matrix.

• eltype=Float64: Element type for X and y. Must subtype AbstractFloat.

• binary=false: Whether the target should be binarized (via a sigmoid).

• eltype=Float64: machine type of points (any subtype of AbstractFloat).

• rng=Random.GLOBAL_RNG: any AbstractRNG object, or integer to seed a MersenneTwister (for reproducibility).

• as_table=true: whether to return the points as a table (true) or a matrix (false).

Example

X, y = make_regression(100, 5; noise=0.5, sparse=0.2, outliers=0.1)