7 #define M_PI 3.14159265358979323846
15 using Centers = std::vector<mltk::Point<double>>;
43 size_t n_loops=2,
double margin = 0.5,
size_t seed = 0);
58 BlobsPair make_blobs(
size_t n_samples=100,
int n_centers=2,
int n_dims=2,
double cluster_std=1.0,
59 double center_min=-10.0,
double center_max=10.0,
bool shuffle=
true,
60 bool has_classes=
true,
size_t seed = 0);
74 std::vector<double> clusters_std,
int n_dims=2,
bool shuffle=
true,
75 bool has_classes=
true,
size_t seed = 0);
89 RegPair make_regression(
size_t n_samples=100,
size_t n_dims=100,
double bias=0.0,
double noise=0.1,
double stdev=0.01,
90 size_t n_informative=10,
bool shuffle=
true,
size_t seed=0);
Namespace for artificial datasets generation.
Definition: Datasets.hpp:14
BlobsPair make_blobs(size_t n_samples=100, int n_centers=2, int n_dims=2, double cluster_std=1.0, double center_min=-10.0, double center_max=10.0, bool shuffle=true, bool has_classes=true, size_t seed=0)
Generate isotropic Gaussian blobs for clustering or classification [source].
Definition: Datasets.cpp:46
mltk::Data< double > make_spirals(size_t n_samples=100, int n_classes=2, bool shuffle=true, double noise=1.0, size_t n_loops=2, double margin=0.5, size_t seed=0)
generates a synthetic data set composed of interlaced Archimedean spirals [source].
Definition: Datasets.cpp:8
RegPair make_regression(size_t n_samples=100, size_t n_dims=100, double bias=0.0, double noise=0.1, double stdev=0.01, size_t n_informative=10, bool shuffle=true, size_t seed=0)
Generate a random regression problem [source].
Definition: Datasets.cpp:110
Definition: Datasets.hpp:24
Centers centers
centers used for points clouds generation
Definition: Datasets.hpp:28
mltk::Data< double > dataset
blobs dataset
Definition: Datasets.hpp:26
Definition: Datasets.hpp:17
mltk::Point< double > coef
true coefficients
Definition: Datasets.hpp:21
mltk::Data< double > dataset
Regression dataset.
Definition: Datasets.hpp:19