Data
MiniBooNE

MiniBooNE

active ARFF Public Domain (CC0) Visibility: public Uploaded 15-08-2018 by Pieter Gijsbers
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This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background). This dataset is ordered. It first contains all signal observations, and then background observations. B. Roe et al., 'Boosted Decision Trees, an Alternative to Artificial Neural Networks' arXiv:physics/0408124, Nucl. Instrum. Meth. A543, 577 (2005).

51 features

signal (target)nominal2 unique values
0 missing
ParticleID_0numeric111368 unique values
0 missing
ParticleID_1numeric110398 unique values
0 missing
ParticleID_2numeric110446 unique values
0 missing
ParticleID_3numeric94548 unique values
0 missing
ParticleID_4numeric16348 unique values
0 missing
ParticleID_5numeric94447 unique values
0 missing
ParticleID_6numeric107776 unique values
0 missing
ParticleID_7numeric98507 unique values
0 missing
ParticleID_8numeric68287 unique values
0 missing
ParticleID_9numeric88422 unique values
0 missing
ParticleID_10numeric68644 unique values
0 missing
ParticleID_11numeric114594 unique values
0 missing
ParticleID_12numeric121900 unique values
0 missing
ParticleID_13numeric118898 unique values
0 missing
ParticleID_14numeric94193 unique values
0 missing
ParticleID_15numeric118540 unique values
0 missing
ParticleID_16numeric117028 unique values
0 missing
ParticleID_17numeric118782 unique values
0 missing
ParticleID_18numeric40019 unique values
0 missing
ParticleID_19numeric115886 unique values
0 missing
ParticleID_20numeric124096 unique values
0 missing
ParticleID_21numeric39401 unique values
0 missing
ParticleID_22numeric121281 unique values
0 missing
ParticleID_23numeric113276 unique values
0 missing
ParticleID_24numeric82961 unique values
0 missing
ParticleID_25numeric125875 unique values
0 missing
ParticleID_26numeric107033 unique values
0 missing
ParticleID_27numeric69277 unique values
0 missing
ParticleID_28numeric93139 unique values
0 missing
ParticleID_29numeric124781 unique values
0 missing
ParticleID_30numeric115505 unique values
0 missing
ParticleID_31numeric101816 unique values
0 missing
ParticleID_32numeric114883 unique values
0 missing
ParticleID_33numeric105461 unique values
0 missing
ParticleID_34numeric117368 unique values
0 missing
ParticleID_35numeric100895 unique values
0 missing
ParticleID_36numeric125172 unique values
0 missing
ParticleID_37numeric109146 unique values
0 missing
ParticleID_38numeric77900 unique values
0 missing
ParticleID_39numeric114710 unique values
0 missing
ParticleID_40numeric81089 unique values
0 missing
ParticleID_41numeric123144 unique values
0 missing
ParticleID_42numeric124144 unique values
0 missing
ParticleID_43numeric119342 unique values
0 missing
ParticleID_44numeric13947 unique values
0 missing
ParticleID_45numeric105274 unique values
0 missing
ParticleID_46numeric125393 unique values
0 missing
ParticleID_47numeric116901 unique values
0 missing
ParticleID_48numeric122183 unique values
0 missing
ParticleID_49numeric93277 unique values
0 missing

62 properties

130064
Number of instances (rows) of the dataset.
51
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.
50
Number of numeric attributes.
1
Number of nominal attributes.
1
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
59.83
First quartile of standard deviation of attributes of the numeric type.
0.86
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
Second quartile (Median) of entropy among attributes.
0
Number of attributes divided by the number of instances.
2
Average number of distinct values among the attributes of the nominal type.
272.88
Second quartile (Median) of kurtosis among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-6.83
Mean skewness among attributes of the numeric type.
-2.82
Second quartile (Median) of means among attributes of the numeric type.
71.94
Percentage of instances belonging to the most frequent class.
965.8
Mean standard deviation of attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
93565
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
-16.58
Second quartile (Median) of skewness among attributes of the numeric type.
Maximum entropy among attributes.
8.79
Minimum kurtosis among attributes of the numeric type.
1.96
Percentage of binary attributes.
59.88
Second quartile (Median) of standard deviation of attributes of the numeric type.
130062.96
Maximum kurtosis among attributes of the numeric type.
-25.23
Minimum of means among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
933.04
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
0
Percentage of missing values.
272.93
Third quartile of kurtosis among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
2
The minimal number of distinct values among attributes of the nominal type.
98.04
Percentage of numeric attributes.
0.85
Third quartile of means among attributes of the numeric type.
2
The maximum number of distinct values among attributes of the nominal type.
-16.58
Minimum skewness among attributes of the numeric type.
1.96
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
360.64
Maximum skewness among attributes of the numeric type.
59.66
Minimum standard deviation of attributes of the numeric type.
First quartile of entropy among attributes.
-16.55
Third quartile of skewness among attributes of the numeric type.
44367.69
Maximum standard deviation of attributes of the numeric type.
28.06
Percentage of instances belonging to the least frequent class.
272.32
First quartile of kurtosis among attributes of the numeric type.
60.17
Third quartile of standard deviation of attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
36499
Number of instances belonging to the least frequent class.
-3.42
First quartile of means among attributes of the numeric type.
2834.99
Mean kurtosis among attributes of the numeric type.
1
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
38.39
Mean of means among attributes of the numeric type.
-16.58
First quartile of skewness among attributes of the numeric type.

4 tasks

0 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: signal
0 runs - estimation_procedure: 10 times 10-fold Crossvalidation - target_feature: signal
0 runs - estimation_procedure: 10-fold Crossvalidation - evaluation_measure: area_under_roc_curve - target_feature: signal
0 runs - estimation_procedure: 50 times Clustering
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