Run 10559856

Task 360880 (Supervised Regression) NASA_PHM2008_1 Uploaded 26-03-2021 by Tan Zheng
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sklearn.tree._classes.ExtraTreeRegressor(1)	An extremely randomized tree regressor. Extra-trees differ from classic decision trees in the way they are built. When looking for the best split to separate the samples of a node into two groups, random splits are drawn for each of the `max_features` randomly selected features and the best split among those is chosen. When `max_features` is set 1, this amounts to building a totally random decision tree. Warning: Extra-trees should only be used within ensemble methods.
sklearn.tree._classes.ExtraTreeRegressor(1)_ccp_alpha	0.0
sklearn.tree._classes.ExtraTreeRegressor(1)_criterion	"mse"
sklearn.tree._classes.ExtraTreeRegressor(1)_max_depth	null
sklearn.tree._classes.ExtraTreeRegressor(1)_max_features	"auto"
sklearn.tree._classes.ExtraTreeRegressor(1)_max_leaf_nodes	null
sklearn.tree._classes.ExtraTreeRegressor(1)_min_impurity_decrease	0.0
sklearn.tree._classes.ExtraTreeRegressor(1)_min_impurity_split	null
sklearn.tree._classes.ExtraTreeRegressor(1)_min_samples_leaf	1
sklearn.tree._classes.ExtraTreeRegressor(1)_min_samples_split	2
sklearn.tree._classes.ExtraTreeRegressor(1)_min_weight_fraction_leaf	0.0
sklearn.tree._classes.ExtraTreeRegressor(1)_random_state	52
sklearn.tree._classes.ExtraTreeRegressor(1)_splitter	"random"

xml

Description

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

arff

Predictions

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

57.2447 ± 0.5923

Cross-validation details (10-fold Crossvalidation)

45918

Cross-validation details (10-fold Crossvalidation)

68.4198 ± 0.6022

Cross-validation details (10-fold Crossvalidation)

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