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Muhammad Sarmad Ali
Doctoral Researcher
University of Limerick Ireland Joined 2021-07-26
0 uploads 0.5 activity 0 reach 0 impact
Simon Tsai
RonAye clinic ?? Joined 2021-07-26
0 uploads 1.5 activity 0 reach 0 impact
Data reported to the police about the circumstances of personal injury road accidents in Great Britain from 1979, and the maker and model information of vehicles involved in the respective accident
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363206 instances - 66 features - 0 classes - 876555 missing values
Data reported to the police about the circumstances of personal injury road accidents in Great Britain from 1979, and the maker and model information of vehicles involved in the respective accident
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Steven Wolk
Self Joined 2021-07-25
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?????? ????????
Thailand Joined 2021-07-25
0 uploads 1 activity 0 reach 0 impact
Vijayakumar M
Research Scholar
SRM IST India Joined 2021-07-24
0 uploads 0.5 activity 0 reach 0 impact
Cristopher Yerena Huescas
Data Scientist
UFRGS México Joined 2021-07-24
0 uploads 0.5 activity 0 reach 0 impact
Appie Kalac
ML master student
TU/e Netherlands Joined 2021-07-22
0 uploads 0.5 activity 0 reach 0 impact
Dr Umer Sohail
PhD in Aerospace Engineering
NUTECH Pakistan Joined 2021-07-22
0 uploads 1 activity 0 reach 0 impact
Lion Alio
Samsung Vietnam Joined 2021-07-22
0 uploads 3.5 activity 0 reach 0 impact
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estimation_procedure : 50 times Clustering - target_feature : class
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estimation_procedure : 50 times Clustering - target_feature : Euclidean Distance
Fabio M
Joined 2021-07-21
0 uploads 0.5 activity 0 reach 0 impact
This is an experimental data set for trying to classify numbers in a lottery as "Highly likely to be picked" or "Not very likely to be picked". It is based on a little more than a…
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12528 instances - 36 features - classes - 0 missing values
ARFF Training Data
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177640 instances - 40 features - classes - 0 missing values
Nick Bobbitt
Barton Malow United States Joined 2021-07-19
1 uploads 1 activity 0 reach 0 impact
Humam Uraibi
Mr UAE Joined 2021-07-19
1 uploads 1 activity 0 reach 0 impact
Benedict Emoe-kabu
University of Benin Nigeria Joined 2021-07-19
0 uploads 3 activity 0 reach 0 impact
Kankshith Reddy
Student
NIT Warangal India Joined 2021-07-16
0 uploads 0 activity 0 reach 0 impact
Online advertisement clicking rates, where the metrics are cost-per-click (CPC) and cost per thousand impressions (CPM).
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1643 instances - 2 features - classes - 0 missing values
Adwait Joshi
Data Scientist
NA India Joined 2021-07-15
0 uploads 1.5 activity 0 reach 0 impact
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estimation_procedure : 50 times Clustering - target_feature : Health
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estimation_procedure : 50 times Clustering
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estimation_procedure : 50 times Clustering
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estimation_procedure : 50 times Clustering
https://archive.ics.uci.edu/ml/datasets/Diabetes
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768 instances - 9 features - classes - 0 missing values
Lukasz Ledzinski
Polska Joined 2021-07-13
0 uploads 0 activity 0 reach 0 impact
CAIQUE FERREIRA
Brasil Joined 2021-07-13
0 uploads 0.5 activity 0 reach 0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7564, kappa: 0.4529, kb_relative_information_score: 0.2812, mean_absolute_error: 0.3365, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7656, number_of_instances: 768, precision: 0.7601, predictive_accuracy: 0.7656, prior_entropy: 0.9331, relative_absolute_error: 0.7404, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4002, root_relative_squared_error: 0.8396, unweighted_recall: 0.7135,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8059, f_measure: 0.7501, kappa: 0.4398, kb_relative_information_score: 0.3214, mean_absolute_error: 0.31, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7578, number_of_instances: 768, precision: 0.7513, predictive_accuracy: 0.7578, prior_entropy: 0.9331, relative_absolute_error: 0.6821, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4107, root_relative_squared_error: 0.8616, unweighted_recall: 0.7093,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7564, kappa: 0.4529, kb_relative_information_score: 0.2812, mean_absolute_error: 0.3365, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7656, number_of_instances: 768, precision: 0.7601, predictive_accuracy: 0.7656, prior_entropy: 0.9331, relative_absolute_error: 0.7404, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4002, root_relative_squared_error: 0.8396, unweighted_recall: 0.7135,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7893, f_measure: 0.7409, kappa: 0.4186, kb_relative_information_score: 0.2942, mean_absolute_error: 0.3203, mean_prior_absolute_error: 0.4545, weighted_recall: 0.75, number_of_instances: 768, precision: 0.7428, predictive_accuracy: 0.75, prior_entropy: 0.9331, relative_absolute_error: 0.7048, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4204, root_relative_squared_error: 0.882, unweighted_recall: 0.6981,
Fabio Lima
freelancer Brasil Joined 2021-07-10
0 uploads 1.5 activity 0 reach 0 impact
Online advertisement clicking rates, where the metrics are cost-per-click (CPC) and cost per thousand impressions (CPM).
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1643 instances - 3 features - classes - 0 missing values
Online advertisement clicking rates, where the metrics are cost-per-click (CPC) and cost per thousand impressions (CPM).
0 runs0 likes0 downloads0 reach0 impact
1538 instances - 3 features - classes - 0 missing values
Online advertisement clicking rates, where the metrics are cost-per-click (CPC) and cost per thousand impressions (CPM).
0 runs0 likes0 downloads0 reach0 impact
1624 instances - 3 features - classes - 0 missing values
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8261, f_measure: 0.7564, kappa: 0.4529, kb_relative_information_score: 0.2812, mean_absolute_error: 0.3365, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7656, number_of_instances: 768, precision: 0.7601, predictive_accuracy: 0.7656, prior_entropy: 0.9331, relative_absolute_error: 0.7404, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4002, root_relative_squared_error: 0.8396, unweighted_recall: 0.7135,
Logistic Regression (aka logit, MaxEnt) classifier. In the multiclass case, the training algorithm uses the one-vs-rest (OvR) scheme if the 'multi_class' option is set to 'ovr', and uses the…
2 runs0 likes0 downloads0 reach0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8081, f_measure: 0.7493, kappa: 0.4384, kb_relative_information_score: 0.3124, mean_absolute_error: 0.3137, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7565, number_of_instances: 768, precision: 0.75, predictive_accuracy: 0.7565, prior_entropy: 0.9331, relative_absolute_error: 0.6902, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4111, root_relative_squared_error: 0.8625, unweighted_recall: 0.7091,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.7964, f_measure: 0.7428, kappa: 0.4232, kb_relative_information_score: 0.2958, mean_absolute_error: 0.3212, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7513, number_of_instances: 768, precision: 0.7442, predictive_accuracy: 0.7513, prior_entropy: 0.9331, relative_absolute_error: 0.7068, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4145, root_relative_squared_error: 0.8696, unweighted_recall: 0.7008,
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…
3 runs0 likes0 downloads0 reach0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9798, f_measure: 0.9637, kappa: 0.9597, kb_relative_information_score: 0.962, mean_absolute_error: 0.0073, mean_prior_absolute_error: 0.18, weighted_recall: 0.9637, number_of_instances: 10992, precision: 0.9637, predictive_accuracy: 0.9637, prior_entropy: 3.3208, relative_absolute_error: 0.0403, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0852, root_relative_squared_error: 0.284, unweighted_recall: 0.9636,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9788, f_measure: 0.9619, kappa: 0.9576, kb_relative_information_score: 0.9601, mean_absolute_error: 0.0076, mean_prior_absolute_error: 0.18, weighted_recall: 0.9619, number_of_instances: 10992, precision: 0.9619, predictive_accuracy: 0.9619, prior_entropy: 3.3208, relative_absolute_error: 0.0424, root_mean_prior_squared_error: 0.3, root_mean_squared_error: 0.0873, root_relative_squared_error: 0.2911, unweighted_recall: 0.9619,
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 fit…
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A decision tree classifier.
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0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.8237, f_measure: 0.7686, kappa: 0.4847, kb_relative_information_score: 0.3096, mean_absolute_error: 0.319, mean_prior_absolute_error: 0.4545, weighted_recall: 0.7721, number_of_instances: 768, precision: 0.7677, predictive_accuracy: 0.7721, prior_entropy: 0.9331, relative_absolute_error: 0.702, root_mean_prior_squared_error: 0.4766, root_mean_squared_error: 0.4007, root_relative_squared_error: 0.8407, unweighted_recall: 0.7358,
Gokul Talele
SSBM India Joined 2021-07-09
9 uploads 9 activity 0 reach 0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9914, f_measure: 0.9693, kappa: 0.9378, kb_relative_information_score: 0.936, mean_absolute_error: 0.0315, mean_prior_absolute_error: 0.4948, weighted_recall: 0.9694, number_of_instances: 14980, precision: 0.9703, predictive_accuracy: 0.9694, prior_entropy: 0.9924, relative_absolute_error: 0.0637, root_mean_prior_squared_error: 0.4974, root_mean_squared_error: 0.1387, root_relative_squared_error: 0.2788, unweighted_recall: 0.9666,
Pedro Virgílio Alves de Araújo Santos
Brasil Joined 2021-07-08
0 uploads 4.5 activity 0 reach 0 impact
Daewon Chung
South Korea Joined 2021-07-07
0 uploads 1 activity 0 reach 0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9934, f_measure: 0.8653, kappa: 0.8567, kb_relative_information_score: 0.7376, mean_absolute_error: 0.0344, mean_prior_absolute_error: 0.074, weighted_recall: 0.8623, number_of_instances: 20000, precision: 0.8775, predictive_accuracy: 0.8623, prior_entropy: 4.6998, relative_absolute_error: 0.4653, root_mean_prior_squared_error: 0.1923, root_mean_squared_error: 0.1128, root_relative_squared_error: 0.5867, unweighted_recall: 0.8616,
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 fit…
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Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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Implementation of the scikit-learn classifier API for Keras.
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Automatically created tensorflow flow.
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estimation_procedure : 50 times Clustering
artificial no anomaly
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4032 instances - 2 features - 0 classes - 0 missing values
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uploader_id : 26700 - estimation_procedure : 5 times 2-fold Crossvalidation - target_feature : Class
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estimation_procedure : 10% Holdout set - target_feature : Class
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.9933, f_measure: 0.8607, kappa: 0.8519, kb_relative_information_score: 0.7361, mean_absolute_error: 0.0343, mean_prior_absolute_error: 0.074, weighted_recall: 0.8576, number_of_instances: 20000, precision: 0.8738, predictive_accuracy: 0.8576, prior_entropy: 4.6998, relative_absolute_error: 0.4632, root_mean_prior_squared_error: 0.1923, root_mean_squared_error: 0.113, root_relative_squared_error: 0.5878, unweighted_recall: 0.8569,
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 fit…
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Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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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 fit…
1 runs0 likes0 downloads0 reach0 impact
Dimensionality reduction using truncated SVD (aka LSA). This transformer performs linear dimensionality reduction by means of truncated singular value decomposition (SVD). Contrary to PCA, this…
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Imputation transformer for completing missing values.
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Encode categorical features as a one-hot numeric array. The input to this transformer should be an array-like of integers or strings, denoting the values taken on by categorical (discrete) features.…
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Automatically created tensorflow flow.
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John Tian
United States Joined 2021-07-06
0 uploads 0.5 activity 0 reach 0 impact
Mohamed El Ghazali Sediki
Cyber Security Analyst , Software Engineer , Machine Learning / Deep Learning
TGL Algeria Joined 2021-07-05
0 uploads 1 activity 0 reach 0 impact
Woundje Djatche
Academically i'm physician bu professionnally i'm data analyst in public health field
Ministry of health Cameroon Joined 2021-07-05
0 uploads 1 activity 0 reach 0 impact
mery
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hi
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hi
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hi
0 runs0 likes0 downloads0 reach0 impact
Prithvi Tilwani
Meal Deal India Joined 2021-07-04
4 uploads 4 activity 0 reach 0 impact
Franz Lorenz
Private Deutschland Joined 2021-07-04
0 uploads 0 activity 0 reach 0 impact
joel lusavuvu
Lussi Technologies Congo-Kinshasa Joined 2021-07-03
0 uploads 1 activity 0 reach 0 impact
Michael Baluja
Joined 2021-07-02
1 uploads 1 activity 0 reach 0 impact
HJ WANG
BANK TW Joined 2021-07-02
0 uploads 0.5 activity 0 reach 0 impact
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estimation_procedure : 5 times 2-fold Crossvalidation - evaluation_measures : precision - target_feature : Class
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 0.2171, mean_absolute_error: 0.0325, mean_prior_absolute_error: 0.0631, weighted_recall: 0.9675, number_of_instances: 4032, predictive_accuracy: 0.9675, prior_entropy: 0.2067, relative_absolute_error: 0.515, root_mean_prior_squared_error: 0.1773, root_mean_squared_error: 0.1803, root_relative_squared_error: 1.0167, unweighted_recall: 0.5,
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uploader_id : 26700 - estimation_procedure : 10-fold Crossvalidation - evaluation_measures : precision - target_feature : Class
Dogukan Kizbay
Physics Master Student Working on Higgs Decays
Eskisehir Technical University Turkey Joined 2021-07-01
0 uploads
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 0.2171, mean_absolute_error: 0.0325, mean_prior_absolute_error: 0.0631, weighted_recall: 0.9675, number_of_instances: 4032, predictive_accuracy: 0.9675, prior_entropy: 0.2067, relative_absolute_error: 0.515, root_mean_prior_squared_error: 0.1773, root_mean_squared_error: 0.1803, root_relative_squared_error: 1.0167, unweighted_recall: 0.5,
Jeffrey Scott Cook
Amgen United States Joined 2021-06-30
0 uploads 2.5 activity 0 reach 0 impact
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 0.2171, mean_absolute_error: 0.0325, mean_prior_absolute_error: 0.0631, weighted_recall: 0.9675, number_of_instances: 4032, predictive_accuracy: 0.9675, prior_entropy: 0.2067, relative_absolute_error: 0.515, root_mean_prior_squared_error: 0.1773, root_mean_squared_error: 0.1803, root_relative_squared_error: 1.0167, unweighted_recall: 0.5,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 0.2171, mean_absolute_error: 0.0325, mean_prior_absolute_error: 0.0631, weighted_recall: 0.9675, number_of_instances: 4032, predictive_accuracy: 0.9675, prior_entropy: 0.2067, relative_absolute_error: 0.515, root_mean_prior_squared_error: 0.1773, root_mean_squared_error: 0.1803, root_relative_squared_error: 1.0167, unweighted_recall: 0.5,
0 likes - 0 downloads - 0 reach - area_under_roc_curve: 0.5, kb_relative_information_score: 0.2171, mean_absolute_error: 0.0325, mean_prior_absolute_error: 0.0631, weighted_recall: 0.9675, number_of_instances: 4032, predictive_accuracy: 0.9675, prior_entropy: 0.2067, relative_absolute_error: 0.515, root_mean_prior_squared_error: 0.1773, root_mean_squared_error: 0.1803, root_relative_squared_error: 1.0167, unweighted_recall: 0.5,
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 fit…
4 runs0 likes0 downloads0 reach0 impact
Encode categorical features as an integer array. The input to this transformer should be an array-like of integers or strings, denoting the values taken on by categorical (discrete) features. The…
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Scale features using statistics that are robust to outliers. This Scaler removes the median and scales the data according to the quantile range (defaults to IQR: Interquartile Range). The IQR is the…
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Classifier implementing the k-nearest neighbors vote.
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Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
0 runs0 likes0 downloads0 reach0 impact
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uploader_id : 869 - estimation_procedure : 10-fold Crossvalidation - target_feature : MEDIAN_PXC50
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uploader_id : 869 - estimation_procedure : 10-fold Crossvalidation - target_feature : MEDIAN_PXC50
Aman Solanki
United States of America Joined 2021-06-29
0 uploads 1 activity 0 reach 0 impact
0 runs0 likes0 downloads0 reach0 impact
estimation_procedure : 50 times Clustering
3 runs0 likes0 downloads0 reach0 impact
uploader_id : 26700 - estimation_procedure : 10-fold Crossvalidation - target_feature : Class
artificial with anomaly
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4032 instances - 3 features - 2 classes - 0 missing values