Data
cmc

cmc

active ARFF Publicly available Visibility: public Uploaded 06-04-2014 by Jan van Rijn
0 likes downloaded by 17 people , 19 total downloads 0 issues 0 downvotes
  • OpenML-CC18 OpenML100 study_1 study_123 study_14 study_34 study_37 study_41 study_50 study_7 study_70 study_98 study_99 uci
Issue #Downvotes for this reason By


Loading wiki
Help us complete this description Edit
Author: [Tjen-Sien Lim](limt@stat.wisc.edu) Source: [As obtained from UCI](https://archive.ics.uci.edu/ml/datasets/Contraceptive+Method+Choice) Please cite: [UCI citation](https://archive.ics.uci.edu/ml/citation_policy.html) 1. Title: Contraceptive Method Choice 2. Sources: (a) Origin: This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey (b) Creator: Tjen-Sien Lim (limt@stat.wisc.edu) (c) Donor: Tjen-Sien Lim (limt@stat.wisc.edu) (c) Date: June 7, 1997 3. Past Usage: Lim, T.-S., Loh, W.-Y. & Shih, Y.-S. (1999). A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-three Old and New Classification Algorithms. Machine Learning. Forthcoming. (ftp://ftp.stat.wisc.edu/pub/loh/treeprogs/quest1.7/mach1317.pdf or (http://www.stat.wisc.edu/~limt/mach1317.pdf) 4. Relevant Information: This dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey. The samples are married women who were either not pregnant or do not know if they were at the time of interview. The problem is to predict the current contraceptive method choice (no use, long-term methods, or short-term methods) of a woman based on her demographic and socio-economic characteristics. 5. Number of Instances: 1473 6. Number of Attributes: 10 (including the class attribute) 7. Attribute Information: 1. Wife's age (numerical) 2. Wife's education (categorical) 1=low, 2, 3, 4=high 3. Husband's education (categorical) 1=low, 2, 3, 4=high 4. Number of children ever born (numerical) 5. Wife's religion (binary) 0=Non-Islam, 1=Islam 6. Wife's now working? (binary) 0=Yes, 1=No 7. Husband's occupation (categorical) 1, 2, 3, 4 8. Standard-of-living index (categorical) 1=low, 2, 3, 4=high 9. Media exposure (binary) 0=Good, 1=Not good 10. Contraceptive method used (class attribute) 1=No-use 2=Long-term 3=Short-term 8. Missing Attribute Values: None Information about the dataset CLASSTYPE: nominal CLASSINDEX: last

10 features

Contraceptive_method_used (target)nominal3 unique values
0 missing
Wifes_agenumeric34 unique values
0 missing
Wifes_educationnominal4 unique values
0 missing
Husbands_educationnominal4 unique values
0 missing
Number_of_children_ever_bornnumeric15 unique values
0 missing
Wifes_religionnominal2 unique values
0 missing
Wifes_now_working%3Fnominal2 unique values
0 missing
Husbands_occupationnominal4 unique values
0 missing
Standard-of-living_indexnominal4 unique values
0 missing
Media_exposurenominal2 unique values
0 missing

19 properties

1473
Number of instances (rows) of the dataset.
10
Number of attributes (columns) of the dataset.
3
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.
2
Number of numeric attributes.
8
Number of nominal attributes.
30
Percentage of binary attributes.
0
Percentage of instances having missing values.
1
Average class difference between consecutive instances.
0
Percentage of missing values.
0.01
Number of attributes divided by the number of instances.
20
Percentage of numeric attributes.
42.7
Percentage of instances belonging to the most frequent class.
80
Percentage of nominal attributes.
629
Number of instances belonging to the most frequent class.
22.61
Percentage of instances belonging to the least frequent class.
333
Number of instances belonging to the least frequent class.
3
Number of binary attributes.

24 tasks

9324 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: Contraceptive_method_used
302 runs - estimation_procedure: 5 times 2-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
300 runs - estimation_procedure: 33% Holdout set - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
175 runs - estimation_procedure: 10 times 10-fold Crossvalidation - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
0 runs - estimation_procedure: 33% Holdout set - target_feature: Contraceptive_method_used
0 runs - estimation_procedure: Leave one out - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
302 runs - estimation_procedure: 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
170 runs - estimation_procedure: 10 times 10-fold Learning Curve - evaluation_measure: predictive_accuracy - target_feature: Contraceptive_method_used
25 runs - estimation_procedure: Interleaved Test then Train - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
1310 runs - target_feature: Contraceptive_method_used
1307 runs - target_feature: Contraceptive_method_used
1303 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
0 runs - target_feature: Contraceptive_method_used
Define a new task