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TimeSeriesSVRTslearn

API referenceSource
Multivariate

Time Series Suppoer Vector Regressor, from tslearn.

Quickstart

python
from sktime.regression.kernel_based import TimeSeriesSVRTslearn

estimator = TimeSeriesSVRTslearn(C=1.0, kernel='gak', degree=3, gamma='auto', coef0=0.0, shrinking=True, tol=0.001, epsilon=0.1, cache_size=200, n_jobs=None, verbose=0, max_iter=-1)

Parameters(12)

Cfloat, optional (default=1.0)
Penalty parameter C of the error term.
kernelstring, optional (default=’gak’)

Specifies the kernel type to be used in the algorithm. It must be one of ‘gak’ or a kernel accepted by sklearn.svm.SVR. If none is given, ‘gak’ will be used. If a callable is given it is used to pre-compute the kernel matrix from data matrices; that matrix should be an array of shape (n_samples, n_samples).

degreeint, optional (default=3)
Degree of the polynomial kernel function (‘poly’). Ignored by all other kernels.
gammafloat, optional (default=’auto’)

Kernel coefficient for ‘gak’, ‘rbf’, ‘poly’ and ‘sigmoid’. If gamma is ‘auto’ then:

  • for ‘gak’ kernel, it is computed based on a sampling of the training set tslearn.metrics.gamma_soft_dtw

  • for other kernels (eg. ‘rbf’), 1/n_features will be used.

coef0float, optional (default=0.0)
Independent term in kernel function. It is only significant in ‘poly’ and ‘sigmoid’.
tolfloat, optional (default=1e-3)
Tolerance for stopping criterion.
epsilonfloat, optional (default=0.1)
Epsilon in the epsilon-SVR model. It specifies the epsilon-tube within which no penalty is associated in the training loss function with points predicted within a distance epsilon from the actual value.
shrinkingboolean, optional (default=True)
Whether to use the shrinking heuristic.
cache_sizefloat, optional (default=200.0)
Specify the size of the kernel cache (in MB).
n_jobsint or None, optional (default=None)

The number of jobs to run in parallel for GAK cross-similarity matrix computations. None means 1 unless in a joblib.parallel_backend context. -1 means using all processors. See scikit-learns’ Glossary for more details.

verboseint, default: 0
Enable verbose output. Note that this setting takes advantage of a per-process runtime setting in libsvm that, if enabled, may not work properly in a multithreaded context.
max_iterint, optional (default=-1)
Hard limit on iterations within solver, or -1 for no limit.