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bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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5000 instances - 32 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#water) - Number of nodes: 32 - Number of arcs: 66 - Number of parameters: 10083 - Average…
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bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#mildew) - Number of nodes: 35 - Number of arcs: 46 - Number of parameters: 540150 -…
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5000 instances - 35 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#insurance) - Number of nodes: 27 - Number of arcs: 52 - Number of parameters: 1008 -…
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5000 instances - 27 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#child) - Number of nodes: 20 - Number of arcs: 25 - Number of parameters: 230 - Average…
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5000 instances - 20 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 48 - Number of arcs: 84 - Number of parameters: 114005 -…
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5000 instances - 48 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
bnlearn Bayesian Network Repository reference: [URL](https://www.bnlearn.com/bnrepository/discrete-medium.html#alarm) - Number of nodes: 37 - Number of arcs: 46 - Number of parameters: 509 - Average…
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5000 instances - 37 features - classes - 0 missing values
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9362, f_measure: 0.8793, kappa: 0.7322, kb_relative_information_score: 0.597, mean_absolute_error: 0.1943, mean_prior_absolute_error: 0.456, weighted_recall: 0.8812, number_of_instances: 19020, precision: 0.8809, predictive_accuracy: 0.8812, prior_entropy: 0.9355, relative_absolute_error: 0.426, root_mean_prior_squared_error: 0.4775, root_mean_squared_error: 0.2996, root_relative_squared_error: 0.6275, unweighted_recall: 0.856,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7801, f_measure: 0.7305, kappa: 0.3933, kb_relative_information_score: 0.2715, mean_absolute_error: 0.3317, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7438, number_of_instances: 7680, precision: 0.7363, predictive_accuracy: 0.7438, prior_entropy: 0.9331, relative_absolute_error: 0.7298, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4211, root_relative_squared_error: 0.8836, unweighted_recall: 0.6828,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7801, f_measure: 0.7305, kappa: 0.3933, kb_relative_information_score: 0.2715, mean_absolute_error: 0.3317, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7438, number_of_instances: 7680, precision: 0.7363, predictive_accuracy: 0.7438, prior_entropy: 0.9331, relative_absolute_error: 0.7298, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4211, root_relative_squared_error: 0.8836, unweighted_recall: 0.6828,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7378, f_measure: 0.7123, kappa: 0.3578, kb_relative_information_score: 0.249, mean_absolute_error: 0.3359, mean_prior_absolute_error: 0.4545, weighted_recall: 0.718, number_of_instances: 7680, precision: 0.7104, predictive_accuracy: 0.718, prior_entropy: 0.9331, relative_absolute_error: 0.739, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4473, root_relative_squared_error: 0.9384, unweighted_recall: 0.6729,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9799, f_measure: 0.9639, kappa: 0.9599, kb_relative_information_score: 0.9622, mean_absolute_error: 0.0072, mean_prior_absolute_error: 0.18, weighted_recall: 0.9639, number_of_instances: 10992, precision: 0.9639, predictive_accuracy: 0.9639, prior_entropy: 3.3208, relative_absolute_error: 0.0401, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.085, root_relative_squared_error: 0.2833, unweighted_recall: 0.9638,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.98, f_measure: 0.964, kappa: 0.96, kb_relative_information_score: 0.9623, mean_absolute_error: 0.0072, mean_prior_absolute_error: 0.18, weighted_recall: 0.964, number_of_instances: 10992, precision: 0.964, predictive_accuracy: 0.964, prior_entropy: 3.3208, relative_absolute_error: 0.04, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0849, root_relative_squared_error: 0.283, unweighted_recall: 0.9639,
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement…
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Imputation transformer for completing missing values.
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A decision tree classifier.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9362, f_measure: 0.8794, kappa: 0.7324, kb_relative_information_score: 0.5969, mean_absolute_error: 0.1944, mean_prior_absolute_error: 0.456, weighted_recall: 0.8814, number_of_instances: 19020, precision: 0.8812, predictive_accuracy: 0.8814, prior_entropy: 0.9355, relative_absolute_error: 0.4264, root_mean_prior_squared_error: 0.4775, root_mean_squared_error: 0.2995, root_relative_squared_error: 0.6273, unweighted_recall: 0.8559,
A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive…
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Context A collection of tweets (in dutch) and features, gathered in april 2022 using the Twitter API. A small portion of the tweets are annotated by volunteer annotators. The main task is to identify…
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451200 instances - 20 features - 0 classes - 0 missing values
This motor third-part liability (MTPL) pricing dataset describes 1 Mio insurance policies and their corresponding claim counts, see Mayer, M., Meier, D. and Wuthrich, M.V. (2023) SHAP for Actuaries:…
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1000000 instances - 7 features - 0 classes - 0 missing values