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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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.. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442…
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442 instances - 11 features - 0 classes - 0 missing values
.. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442…
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442 instances - 11 features - 0 classes - 0 missing values
.. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442…
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442 instances - 11 features - 0 classes - 0 missing values
.. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442…
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442 instances - 11 features - 0 classes - 0 missing values
.. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442…
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442 instances - 11 features - 0 classes - 0 missing values
.. _diabetes_dataset: Diabetes dataset ---------------- Ten baseline variables, age, sex, body mass index, average blood pressure, and six blood serum measurements were obtained for each of n = 442…
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442 instances - 11 features - 0 classes - 0 missing values
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : Class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : readmitted
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : Class
Test dataset
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Test dataset
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iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - 3 classes - 0 missing values
iris with ignored features Sepal.Width and Petal.Length
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150 instances - 5 features - classes - 0 missing values
Jed Brewer
Canada Joined 2019-03-20
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Automatically created shogun flow.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.732, f_measure: 0.7538, kappa: 0.4915, kb_relative_information_score: 2597.7783, mean_absolute_error: 0.2328, mean_prior_absolute_error: 0.4849, number_of_instances: 5060, precision: 0.7846, predictive_accuracy: 0.7672, prior_entropy: 0.9782, recall: 0.7672, relative_absolute_error: 0.4801, root_mean_prior_squared_error: 0.4924, root_mean_squared_error: 0.4825, root_relative_squared_error: 0.9799,
Learner mlr.classif.ranger.preproc from package(s) ranger.
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Learner mlr.classif.ranger.preproc from package(s) ranger.
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Learner mlr.classif.ranger.preproc from package(s) ranger.
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Learner mlr.classif.ranger from package(s) ranger.
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Learner mlr.classif.ranger.preproc from package(s) ranger.
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Learner mlr.classif.ranger.preproc from package(s) ranger.
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Philipp Danzinger
Joined 2019-03-19
1 uploads 1 activity 0 reach 0 impact
Learner mlr.classif.ranger.preproc from package(s) ranger.
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : character
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : Class
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estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : Class
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : confusion_matrix,predictive_accuracy,area_under_roc_curve - target_feature : class
Juan Tafarello
Acciona España Joined 2019-03-19
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estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : Tmax
Testing this plattform
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36203 instances - 18 features - 0 classes - 8971 missing values
Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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estimation_procedure : 10-fold Crossvalidation - target_feature : class
nfc3
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nfc2
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Akram Mustafa
James Cook University Australia Joined 2019-03-18
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Juan Sebastián Peláez Villa
Universidad de Antioquia Colombia Joined 2019-03-17
0 uploads 0.5 activity 0 reach 0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5379, f_measure: 0.4818, kappa: 0.0615, kb_relative_information_score: 0.0712, mean_absolute_error: 0.4641, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.5494, predictive_accuracy: 0.5307, prior_entropy: 1, recall: 0.5307, relative_absolute_error: 0.9283, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6696, root_relative_squared_error: 1.3392,
D. Aha, D. Kibler (1991). Instance-based learning algorithms. Machine Learning. 6:37-66.
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Weka implementation.
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Wikipedia. Euclidean distance. URL http://en.wikipedia.org/wiki/Euclidean_distance.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7626, f_measure: 0.7626, kappa: 0.5251, kb_relative_information_score: 0.5251, mean_absolute_error: 0.2374, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.7626, predictive_accuracy: 0.7626, prior_entropy: 1, recall: 0.7626, relative_absolute_error: 0.4749, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4873, root_relative_squared_error: 0.9745,
Weka implementation.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7127, f_measure: 0.6871, kappa: 0.3743, kb_relative_information_score: 0.2251, mean_absolute_error: 0.4015, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.6872, predictive_accuracy: 0.6872, prior_entropy: 1, recall: 0.6872, relative_absolute_error: 0.8029, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4612, root_relative_squared_error: 0.9225,
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7318, f_measure: 0.6811, kappa: 0.3631, kb_relative_information_score: 91.5914, mean_absolute_error: 0.3825, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.6827, predictive_accuracy: 0.6816, prior_entropy: 1, recall: 0.6816, relative_absolute_error: 0.7651, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.466, root_relative_squared_error: 0.932,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8026, f_measure: 0.7372, kappa: 0.4749, kb_relative_information_score: 0.1319, mean_absolute_error: 0.4482, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.7382, predictive_accuracy: 0.7374, prior_entropy: 1, recall: 0.7374, relative_absolute_error: 0.8963, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.4564, root_relative_squared_error: 0.9128,
Leo Breiman (2001). Random Forests. Machine Learning. 45(1):5-32.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6847, f_measure: 0.6423, kappa: 0.2849, kb_relative_information_score: 0.2892, mean_absolute_error: 0.3552, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.6427, predictive_accuracy: 0.6425, prior_entropy: 1, recall: 0.6425, relative_absolute_error: 0.7104, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5698, root_relative_squared_error: 1.1397,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.6369, f_measure: 0.6124, kappa: 0.2737, kb_relative_information_score: 0.2737, mean_absolute_error: 0.3631, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.6832, predictive_accuracy: 0.6369, prior_entropy: 1, recall: 0.6369, relative_absolute_error: 0.7263, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.6026, root_relative_squared_error: 1.2052,
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.495, f_measure: 0.4002, kappa: -0.0056, kb_relative_information_score: -0.0089, mean_absolute_error: 0.5, mean_prior_absolute_error: 0.5, number_of_instances: 358, precision: 0.4921, predictive_accuracy: 0.4972, prior_entropy: 1, recall: 0.4972, relative_absolute_error: 1, root_mean_prior_squared_error: 0.5, root_mean_squared_error: 0.5, root_relative_squared_error: 1,
Weka implementation.
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Weka implementation.
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uploader_id : 1 - estimation_procedure : Test on Training Data - target_feature : class
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uploader_id : 1 - estimation_procedure : 33% Holdout set - target_feature : class
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uploader_id : 1 - estimation_procedure : 10% Holdout set - target_feature : class
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uploader_id : 1 - estimation_procedure : Leave one out - target_feature : class
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uploader_id : 1 - estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
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uploader_id : 1 - estimation_procedure : 5 times 2-fold Crossvalidation - target_feature : class
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uploader_id : 1 - estimation_procedure : 10-fold Crossvalidation - target_feature : class
Ya?ar Dereli
Software Engineer, Oracle DBA,
Dokuz Eylul University Türkiye Joined 2019-03-16
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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Automatically created scikit-learn flow.
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This dataset contains 358 lyrics of songs for the rock bands 'The Rolling Stones' and 'Deep Purple'. The bands are equally represented in the dataset (179 songs for each band). This dataset was…
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358 instances - 2 features - 2 classes - 0 missing values
sunil sunny
not yet working still studying
ifhe hyderabad india Joined 2019-03-15
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Learner mlr.classif.randomForest from package(s) randomForest.
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Fernando José Duarte
University of Aveiro Portugal Joined 2019-03-15
9 uploads 9 activity 1 reach 8 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.803, f_measure: 0.8126, kappa: 0.6119, kb_relative_information_score: 3088.7902, mean_absolute_error: 0.1864, mean_prior_absolute_error: 0.4849, number_of_instances: 5060, precision: 0.8128, predictive_accuracy: 0.8136, prior_entropy: 0.9782, recall: 0.8136, relative_absolute_error: 0.3843, root_mean_prior_squared_error: 0.4924, root_mean_squared_error: 0.4317, root_relative_squared_error: 0.8768,