Data
NEERI

NEERI

active ARFF Public Domain (CC0) Visibility: public Uploaded 03-10-2020 by Arshad Shareef
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This data is used to test water contamination

8 features

temperaturenumeric6 unique values
0 missing
pHnumeric3 unique values
0 missing
conductivitynumeric19 unique values
0 missing
bodnumeric14 unique values
0 missing
faecialcolinumeric9 unique values
0 missing
totalcolinumeric11 unique values
0 missing
nitratenumeric19 unique values
0 missing
classnominal2 unique values
0 missing

19 properties

26
Number of instances (rows) of the dataset.
8
Number of attributes (columns) of the dataset.
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.
7
Number of numeric attributes.
1
Number of nominal attributes.
0.31
Number of attributes divided by the number of instances.
87.5
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
12.5
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
1
Number of binary attributes.
12.5
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

9 tasks

0 runs - estimation_procedure: Test on Training Data - evaluation_measure: temperature, pH, conductivity, bod, faecialcoli, totalcoli, nitrate, - 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 - evaluation_measure: predictive_accuracy - 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 - evaluation_measure: predictive_accuracy - target_feature: class
0 runs - estimation_procedure: 10-fold Learning Curve - target_feature: class
0 runs - estimation_procedure: Interleaved Test then Train - target_feature: class
0 runs - estimation_procedure: 50 times Clustering
0 runs - estimation_procedure: 50 times Clustering
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