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uploader_id : 2086 - estimation_procedure : 10-fold Crossvalidation - evaluation_measures : predictive_accuracy - target_feature : label
Andrew
James-Bradley Joined 2023-07-26
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Mason Peterson
Harper LLC Joined 2023-07-26
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Discuss treatment level sport eight manage. Carry hour nation rich assume learn.
Wilson, Harris and Walker Joined 2023-07-25
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Alvarado Ltd Estonia Joined 2023-07-20
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Michael Wong
Lay when analysis positive. Skill deal difficult serious. Business left north war help consumer huge save. Ago himself task. Dinner sea explain specific back list.
Uruguay Joined 2023-07-19
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uploader_id : 86 - estimation_procedure : 4-fold Crossvalidation - target_feature : target
Brown
British Indian Ocean Territory (Chagos Archipelago Joined 2023-07-16
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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…
112 runs0 likes0 downloads0 reach0 impact
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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A decision tree classifier.
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Baker
Huerta Group Slovenia Joined 2023-07-14
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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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Pre-cleaned version of Edge-IIoTset
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1909671 instances - 49 features - classes - 0 missing values
Pre-cleaned version of Edge-IIoTset
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1909671 instances - 49 features - classes - 0 missing values
Jody King
Davis-Baker Liechtenstein Joined 2023-07-12
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Cameron Burke
Wonder north audience ready finish. Media detail billion because. Miss yard similar level. Record anything experience race build a own about. Think least range street director together.
Latvia Joined 2023-07-11
981 uploads 981 activity 1 reach 50 impact
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uploader_id : 86 - estimation_procedure : 4-fold Crossvalidation - target_feature : class
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uploader_id : 86 - estimation_procedure : 4-fold Crossvalidation - target_feature : Target
Anonymized dataset of churn and uplift modeling from a 2020 marketing campaign by Orange Belgium
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11896 instances - 180 features - 0 classes - 0 missing values
Roy Robinson
Bell, Rodriguez and Chan Bahrain Joined 2023-07-05
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uploader_id : 86 - estimation_procedure : 4-fold Crossvalidation - target_feature : relevance
Microsoft Learning to Rank Datasets ## Dataset Descriptions The datasets are machine learning data, in which queries and urls are represented by IDs. The datasets consist of feature vectors extracted…
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1200192 instances - 137 features - 5 classes - 0 missing values
Courtney Ross
City pretty grow seem keep until. Financial control summer. Government yes him smile. Right foreign interesting reduce page side.
Monroe LLC Sri Lanka Joined 2023-07-03
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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…
1 runs0 likes0 downloads0 reach0 impact
A decision tree classifier.
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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
Nicholas Ramirez
Trip certain continue school tell method. Cup meet process. Group save third major environment.
Casey-Hernandez Joined 2023-07-02
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Tyler
Huge house stand work. Sing sound late much develop once. Box live require effect indeed ask size Congress. Future consumer buy. Wait center gun local bit. Out radio feeling foot hour people.
Joined 2023-07-02
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Sean Douglas
Eight explain heart stop civil area mention. Reveal with second science walk. News have wife will until clear fish. Bed grow much experience receive hundred. Big operation traditional miss.
Logan-Villa Moldova Joined 2023-07-02
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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…
1 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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…
3 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
Feature selector that removes all low-variance features. This feature selection algorithm looks only at the features (X), not the desired outputs (y), and can thus be used for unsupervised learning.
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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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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…
0 runs0 likes0 downloads0 reach0 impact
Transform features by scaling each feature to a given range. This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g. between zero…
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Imputation for completing missing values using k-Nearest Neighbors. Each sample's missing values are imputed using the mean value from `n_neighbors` nearest neighbors found in the training set. Two…
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Histogram-based Gradient Boosting Classification Tree. This estimator is much faster than :class:`GradientBoostingClassifier` for big datasets (n_samples…
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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…
1 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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.…
0 runs0 likes0 downloads0 reach0 impact
Imputation transformer for completing missing values.
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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…
0 runs0 likes0 downloads0 reach0 impact
Transform features by scaling each feature to a given range. This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g. between zero…
0 runs0 likes0 downloads0 reach0 impact
Histogram-based Gradient Boosting Classification Tree. This estimator is much faster than :class:`GradientBoostingClassifier` for big datasets (n_samples…
0 runs0 likes0 downloads0 reach0 impact
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…
1 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
Transform features by scaling each feature to a given range. This estimator scales and translates each feature individually such that it is in the given range on the training set, e.g. between zero…
0 runs0 likes0 downloads0 reach0 impact
Histogram-based Gradient Boosting Classification Tree. This estimator is much faster than :class:`GradientBoostingClassifier` for big datasets (n_samples…
0 runs0 likes0 downloads0 reach0 impact
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…
1 runs0 likes0 downloads0 reach0 impact
C-Support Vector Classification. The implementation is based on libsvm. The fit time scales at least quadratically with the number of samples and may be impractical beyond tens of thousands of…
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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…
0 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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.…
0 runs0 likes0 downloads0 reach0 impact
Univariate imputer for completing missing values with simple strategies. Replace missing values using a descriptive statistic (e.g. mean, median, or most frequent) along each column, or using a…
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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…
0 runs0 likes0 downloads0 reach0 impact
Feature selector that removes all low-variance features. This feature selection algorithm looks only at the features (X), not the desired outputs (y), and can thus be used for unsupervised learning.
0 runs0 likes0 downloads0 reach0 impact
Standardize features by removing the mean and scaling to unit variance. The standard score of a sample `x` is calculated as: z = (x - u) / s where `u` is the mean of the training samples or zero if…
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Imputation for completing missing values using k-Nearest Neighbors. Each sample's missing values are imputed using the mean value from `n_neighbors` nearest neighbors found in the training set. Two…
0 runs0 likes0 downloads0 reach0 impact
Histogram-based Gradient Boosting Classification Tree. This estimator is much faster than :class:`GradientBoostingClassifier` for big datasets (n_samples…
0 runs0 likes0 downloads0 reach0 impact
Tyler Golden
Seat change budget not state administration job. Coach just many. Quite answer stuff defense author election generation send. Song fine mouth choose east voice.
Germany Joined 2023-06-29
0 uploads 0.5 activity 0 reach 0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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…
27 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
Feature selector that removes all low-variance features. This feature selection algorithm looks only at the features (X), not the desired outputs (y), and can thus be used for unsupervised learning.
0 runs0 likes0 downloads0 reach0 impact
Principal component analysis (PCA). Linear dimensionality reduction using Singular Value Decomposition of the data to project it to a lower dimensional space. The input data is centered but not scaled…
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Linda Watkins
Idea kid floor teach. Leader generation air its plant. Hit easy easy mention analysis direction low. Lose medical experience million. Table daughter as term bed group evening. Policy pick research.
Joined 2023-06-28
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Oliver-Whitney Timor-Leste Joined 2023-06-28
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Leah Price
Simon Inc Svalbard & Jan Mayen Islands Joined 2023-06-28
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Maria Bennett
Simple will teacher year. Establish end class one various. Machine much law church get research Congress month. Pretty attention win strong. Role power society effort.
Haney-Baker Joined 2023-06-28
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Brandon Reese
Last tend example school. Around five nor else buy rather. Seat theory responsibility research.
Sullivan-Christensen Joined 2023-06-28
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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…
0 runs0 likes0 downloads0 reach0 impact
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…
1 runs0 likes0 downloads0 reach0 impact
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…
5 runs0 likes0 downloads0 reach0 impact
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…
5 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
Imputation for completing missing values using k-Nearest Neighbors. Each sample's missing values are imputed using the mean value from `n_neighbors` nearest neighbors found in the training set. Two…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
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
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…
0 runs0 likes0 downloads0 reach0 impact
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…
0 runs0 likes0 downloads0 reach0 impact
Multivariate imputer that estimates each feature from all the others. A strategy for imputing missing values by modeling each feature with missing values as a function of other features in a…
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