Run
10559853

Run 10559853

Task 4794 (Supervised Regression) cristalli Uploaded 26-03-2021 by Tan Zheng
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Flow

sklearn.svm._classes.SVR(1)Epsilon-Support Vector Regression. The free parameters in the model are C and epsilon. The implementation is based on libsvm. The fit time complexity is more than quadratic with the number of samples which makes it hard to scale to datasets with more than a couple of 10000 samples. For large datasets consider using :class:`sklearn.svm.LinearSVR` or :class:`sklearn.linear_model.SGDRegressor` instead, possibly after a :class:`sklearn.kernel_approximation.Nystroem` transformer.
sklearn.svm._classes.SVR(1)_C1.0
sklearn.svm._classes.SVR(1)_cache_size200
sklearn.svm._classes.SVR(1)_coef00.0
sklearn.svm._classes.SVR(1)_degree3
sklearn.svm._classes.SVR(1)_epsilon0.1
sklearn.svm._classes.SVR(1)_gamma"scale"
sklearn.svm._classes.SVR(1)_kernel"rbf"
sklearn.svm._classes.SVR(1)_max_iter-1
sklearn.svm._classes.SVR(1)_shrinkingtrue
sklearn.svm._classes.SVR(1)_tol0.001
sklearn.svm._classes.SVR(1)_verbosefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

7 Evaluation measures

0.1809 ± 0.0912
Cross-validation details (10-fold Crossvalidation)
32
Cross-validation details (10-fold Crossvalidation)
0.2705 ± 0.149
Cross-validation details (10-fold Crossvalidation)