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Steven Miller
Mendoza LLC Wallis and Futuna Joined 2023-08-16
0 uploads 0 activity 0 reach 0 impact
vonfry-test-collection
test
1 datasets, 1 tasks, 0 flows, 0 runs
vonfry-test-flow (1)
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…
1 runs0 likes0 downloads0 reach0 impact
Supervised Classification on credit-g
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uploader_id : 37411 - estimation_procedure : 10-fold Crossvalidation - target_feature : vonfry-test
sklearn.neighbors._classification.KNeighborsClassifier (22)
Classifier implementing the k-nearest neighbors vote.
1 runs0 likes0 downloads0 reach0 impact
Supervised Regression on rossmann_store_sales
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uploader_id : 37379 - estimation_procedure : 10-fold Crossvalidation - evaluation_measures : root_mean_squared_error - target_feature : Sales
rossmann_store_sales (1)
Rossmann Store Sales from Kaggle with some pre-processing
0 runs0 likes0 downloads0 reach0 impact
804056 instances - 18 features - 0 classes - 0 missing values
Patterson
Care exist it. Design memory company director need. White pressure perhaps a rate. Moment finish real most. World green month star detail success. A country sport stuff toward.
Tucker-Sherman Joined 2023-08-12
0 uploads 0 activity 0 reach 0 impact
Mario
Natural tax civil cover already. Central single number. Along character such beautiful official senior write television.
Ochoa, Moore and Bennett Belgium Joined 2023-08-12
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Supervised Regression on rossmann_store_sales_processed
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uploader_id : 34410 - estimation_procedure : 10-fold Crossvalidation - evaluation_measures : root_mean_squared_error - target_feature : Sales
rossmann_store_sales_processed (1)
Rossmann Store Sales from Kaggle processed
0 runs0 likes0 downloads0 reach0 impact
804056 instances - 18 features - 1 classes - 0 missing values
1
1
1 datasets, 1 tasks, 0 flows, 0 runs
sklearn.neighbors._classification.KNeighborsClassifier (21)
Classifier implementing the k-nearest neighbors vote.
3 runs0 likes0 downloads0 reach2 impact
Kelly Wilson
None brother say each. Art field protect enter. Will mean surface whatever miss account suddenly often. Television may food world tax.
Wright Group Joined 2023-08-08
0 uploads 0.5 activity 0 reach 0 impact
Weather (51)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (50)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37230 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (49)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37222 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37230 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (48)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (47)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37223 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (46)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
0 runs0 likes0 downloads0 reach0 impact
uploader_id : 37230 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (45)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
David
Williams, Harper and Barnes Falkland Islands (Malvinas) Joined 2023-08-07
0 uploads 0 activity 0 reach 0 impact
Test
1)BUY #BANKNIFTY 45300 PE ABOVE -490 TARGET- 40 /70/100/200/250 Point SL-450 2)BUY #BANKNIFTY 45300 PE ABOVE -550 TARGET- 40 /70/100/200/250 Point SL-500 3)BUY#ALKEM 4100 CE ABOVE -218 TARGE- 228,250…
1 datasets, 1 tasks, 0 flows, 0 runs
Test
1)BUY #BANKNIFTY 45300 PE ABOVE -490 TARGET- 40 /70/100/200/250 Point SL-450 2)BUY #BANKNIFTY 45300 PE ABOVE -550 TARGET- 40 /70/100/200/250 Point SL-500 3)BUY#ALKEM 4100 CE ABOVE -218 TARGE- 228,250…
1 datasets, 1 tasks, 0 flows, 0 runs
sklearn.pipeline.Pipeline(variancethreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,randomforestclassifier=sklearn.ensemble._forest.RandomForestClassifier) (1)
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
Weather (44)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (43)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37178 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (42)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
SquareF (1)
simple Math Function
0 runs0 likes0 downloads0 reach0 impact
1000 instances - 2 features - 0 classes - 0 missing values
Weather (41)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on appendicitis_test_edsa
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37163 - estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
appendicitis_test_edsa (3)
appendicities from edsa yang lain lain -- local computer
1 runs0 likes0 downloads0 reach0 impact
106 instances - 8 features - 2 classes - 0 missing values
Weather (40)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on appendicitis_test_edsa
0 runs0 likes0 downloads0 reach0 impact
uploader_id : 37163 - estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
Supervised Classification on Weather
2 runs0 likes0 downloads0 reach0 impact
uploader_id : 37177 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
appendicitis_test_edsa (2)
appendicities from edsa yang lain lain -- local computer
0 runs0 likes0 downloads0 reach0 impact
106 instances - 8 features - 2 classes - 0 missing values
Weather (39)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
2 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37184 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37183 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Supervised Classification on Weather-Test
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37164 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37159 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather-Test (2)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37185 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather-Test (1)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.preprocessing._data.StandardScaler,nominal=sklearn.preprocessing._encoders.OneHotEncoder),variancethreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,randomforestclassifier=sklearn.ensemble._forest.RandomForestClassifier) (3)
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…
9 runs0 likes0 downloads0 reach8 impact
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.preprocessing._data.StandardScaler,nominal=sklearn.preprocessing._encoders.OneHotEncoder) (3)
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
sklearn.preprocessing._data.StandardScaler (19)
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…
0 runs0 likes0 downloads0 reach0 impact
sklearn.feature_selection._variance_threshold.VarianceThreshold (14)
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
sklearn.ensemble._forest.RandomForestClassifier (34)
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 reach3 impact
Weather (38)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (37)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37190 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (36)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (35)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (34)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
dummy (1)
randomly create description
0 runs0 likes0 downloads0 reach0 impact
1000 instances - 7 features - 2 classes - 0 missing values
Supervised Classification on Weather
1 runs0 likes0 downloads0 reach0 impact
uploader_id : 37152 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Child_Growth (1)
tbd
0 runs0 likes0 downloads0 reach0 impact
80000 instances - 20 features - classes - 0 missing values
Supervised Classification on Weather
0 runs0 likes0 downloads0 reach0 impact
uploader_id : 37171 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (33)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (32)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (31)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (30)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
1 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (29)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (28)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (27)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (26)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Weather (25)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Student-Scores (1)
tbd
0 runs0 likes0 downloads0 reach0 impact
56 instances - 13 features - 0 classes - 0 missing values
Weather (24)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Supervised Classification on appendicitis_test_edsa
0 runs0 likes0 downloads0 reach0 impact
uploader_id : 37163 - estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : class
appendicitis_test_edsa (1)
appendicities from edsa yang lain -- local computer
0 runs0 likes0 downloads0 reach0 impact
106 instances - 8 features - 0 classes - 0 missing values
Weather (23)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
0 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
appendicitis_test (2)
appendicities from edsa - local computer
0 runs0 likes0 downloads0 reach0 impact
106 instances - 8 features - 0 classes - 0 missing values
Supervised Classification on appendicitis_test
0 runs0 likes0 downloads0 reach0 impact
uploader_id : 37163 - estimation_procedure : 10 times 10-fold Crossvalidation - target_feature : target
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.preprocessing._data.StandardScaler,nominal=sklearn.preprocessing._encoders.OneHotEncoder),variancethreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,randomforestclassifier=sklearn.ensemble._forest.RandomForestClassifier) (2)
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
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.preprocessing._data.StandardScaler,nominal=sklearn.preprocessing._encoders.OneHotEncoder) (2)
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
sklearn.preprocessing._data.StandardScaler (18)
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…
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing._encoders.OneHotEncoder (49)
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
sklearn.feature_selection._variance_threshold.VarianceThreshold (13)
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
sklearn.ensemble._forest.RandomForestClassifier (33)
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…
0 runs0 likes0 downloads0 reach0 impact
appendicitis_test (1)
appendicities from edsa - local computer
0 runs0 likes0 downloads0 reach0 impact
106 instances - 8 features - 0 classes - 0 missing values
Supervised Classification on Weather
2 runs0 likes0 downloads0 reach0 impact
uploader_id : 37152 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (22)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
2 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
Bank-Churn (1)
tbd
0 runs0 likes0 downloads0 reach0 impact
10000 instances - 14 features - 0 classes - 0 missing values
Supervised Classification on Weather
0 runs0 likes0 downloads0 reach0 impact
uploader_id : 37163 - estimation_procedure : 5 times 2-fold Crossvalidation - target_feature : play
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.preprocessing._data.StandardScaler,nominal=sklearn.preprocessing._encoders.OneHotEncoder),variancethreshold=sklearn.feature_selection._variance_threshold.VarianceThreshold,randomforestclassifier=sklearn.ensemble._forest.RandomForestClassifier) (1)
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…
6 runs0 likes0 downloads0 reach4 impact
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.preprocessing._data.StandardScaler,nominal=sklearn.preprocessing._encoders.OneHotEncoder) (1)
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
sklearn.preprocessing._data.StandardScaler (17)
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…
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing._encoders.OneHotEncoder (48)
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
sklearn.feature_selection._variance_threshold.VarianceThreshold (12)
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
Supervised Classification on Weather
2 runs0 likes0 downloads0 reach0 impact
uploader_id : 37163 - estimation_procedure : 10-fold Crossvalidation - target_feature : play
Weather (21)
The weather problem is a tiny dataset that we will use repeatedly to illustrate machine learning methods. Entirely fictitious, it supposedly concerns the conditions that are suitable for playing some…
2 runs0 likes0 downloads0 reach0 impact
14 instances - 5 features - 2 classes - 0 missing values
sklearn.ensemble._forest.RandomForestClassifier (32)
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…
9 runs0 likes0 downloads0 reach8 impact