BNG(heart-statlog)
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14 features
class (target) | nominal | 2 unique values 0 missing | |
age | numeric | 983895 unique values 0 missing | |
sex | numeric | 2 unique values 0 missing | |
chest | numeric | 216199 unique values 0 missing | |
resting_blood_pressure | numeric | 989437 unique values 0 missing | |
serum_cholestoral | numeric | 996678 unique values 0 missing | |
fasting_blood_sugar | numeric | 2 unique values 0 missing | |
resting_electrocardiographic_results | numeric | 3 unique values 0 missing | |
maximum_heart_rate_achieved | numeric | 993224 unique values 0 missing | |
exercise_induced_angina | numeric | 2 unique values 0 missing | |
oldpeak | numeric | 612925 unique values 0 missing | |
slope | numeric | 3 unique values 0 missing | |
number_of_major_vessels | numeric | 4 unique values 0 missing | |
thal | numeric | 3 unique values 0 missing | |
19 properties
1000000
Number of instances (rows) of the dataset.
14
Number of attributes (columns) of the dataset.
2
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
13
Number of numeric attributes.
1
Number of nominal attributes.
1
Number of binary attributes.
7.14
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0.51
Average class difference between consecutive instances.
92.86
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
55.59
Percentage of instances belonging to the most frequent class.
7.14
Percentage of nominal attributes.
555946
Number of instances belonging to the most frequent class.
44.41
Percentage of instances belonging to the least frequent class.
444054
Number of instances belonging to the least frequent class.
24 tasks
21 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: precision - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
305 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
Define a new task