Merge Interviews

Original KNeTs WBQ

HH9 POOR M
HH8 POOR M
HH7 POOR M
HH6 rich M
HH6 rich F
HH6 POOR M
HH6 POOR F
HH5 rich M
HH5 rich F
HH5 POOR M
HH5 POOR F
HH4 rich M
HH4 rich F
HH4 POOR M
HH4 POOR F
HH3 rich M
HH3 rich F
HH3 POOR M
HH3 POOR F
HH2 rich M
HH2 rich F
HH2 POOR M
HH2 POOR F
HH1 rich M
HH1 rich F
HH1 POOR M
HH1 POOR F

Show Weka Input Weka options Goal variable Select Variables to include:
1. Participantid 2. Gender 3. Climate driver 4. Economic driver 5. Social driver 6. Cocoa (add crop) 7. Plantain (add crop) 8. Macabo (add crop) 9. Coffee (add crop) 10. Palm oil tree (add crop) 11. Cassava, groundnuts and maize (add crop) 12. Sugar cane (add crop) 13. Pineapple (add crop) 14. Potatoes, igname (add crop) 15. Beans (add crop) 16. Melon (add crop) 17. Chilli (add crop) 18. Plant NTFP Trees (add) 19. Plant fruit trees (add) 20. Collect Mempa 21. Collect Djansang, Koko, Djembe and Bush mango 22. Collect Kola 23. Collect Talala 24. Collect Assa 25. Collect Dogote 26. Collect mushrooms, wild honey 27. Grow vegetables 28. Intensify agr. prod. (seeds, fert/pest, improved practices) 29. Make local alcohol 30. Exchange goods/money 31. Do artisanal mining 32. Collect caterpillars/snails 33. Hunt/fish 34. Pisciculture/aquaculture 35. Livestock Keeping 36. Other (additional crop/tree) 37. Other strategy Goals

Options specific to weka.classifiers.trees.J48:

-U Use unpruned tree.
-O Do not collapse tree.
-C [pruning confidence]
	Set confidence threshold for pruning.
	(default 0.25)
-M 
	Set minimum number of instances per leaf.
	(default 2)
-R Use reduced error pruning.
-N [number of folds]
	Set number of folds for reduced error
	pruning. One fold is used as pruning set.
	(default 3)
-B Use binary splits only.
-S Don't perform subtree raising.
-L Do not clean up after the tree has been built.
-A Laplace smoothing for predicted probabilities.
-J Do not use MDL correction for info gain on numeric attributes.
-Q [seed]
	Seed for random data shuffling (default 1).

General options:

-h or -help
	Output help information.
-synopsis or -info
	Output synopsis for classifier (use in conjunction  with -h)
-t [name of training file]
	Sets training file.
-T [name of test file]
	Sets test file. If missing, a cross-validation will be performed
	on the training data.
-c [class index]
	Sets index of class attribute (default: last).
-x [number of folds]
	Sets number of folds for cross-validation (default: 10).
-no-cv
	Do not perform any cross validation.
-split-percentage [percentage]
	Sets the percentage for the train/test set split, e.g., 66.
-preserve-order
	Preserves the order in the percentage split.
-s [random number seed]
	Sets random number seed for cross-validation or percentage split
	(default: 1).
-m [name of file with cost matrix]
	Sets file with cost matrix.
-disable [comma-separated list of evaluation metric names]
	Comma separated list of metric names not to print to the output.
	Available metrics:
	Correct,Incorrect,Kappa,Total cost,Average cost,KB relative,KB information,
	Correlation,Complexity 0,Complexity scheme,Complexity improvement,
	MAE,RMSE,RAE,RRSE,Coverage,Region size,TP rate,FP rate,Precision,Recall,
	F-measure,MCC,ROC area,PRC area
-l [name of input file]
	Sets model input file. In case the filename ends with '.xml',
	a PMML file is loaded or, if that fails, options are loaded
	from the XML file.
-d [name of output file]
	Sets model output file. In case the filename ends with '.xml',
	only the options are saved to the XML file, not the model.
-v Outputs no statistics for training data.
-o Outputs statistics only, not the classifier.
-i Outputs detailed information-retrieval statistics for each class.
-k Outputs information-theoretic statistics.
-classifications "weka.classifiers.evaluation.output.prediction.AbstractOutput + options"
	Uses the specified class for generating the classification output.
	E.g.: weka.classifiers.evaluation.output.prediction.PlainText
-p range
	Outputs predictions for test instances (or the train instances if
	no test instances provided and -no-cv is used), along with the 
	attributes in the specified range (and nothing else). 
	Use '-p 0' if no attributes are desired.
	Deprecated: use "-classifications ..." instead.
-distribution
	Outputs the distribution instead of only the prediction
	in conjunction with the '-p' option (only nominal classes).
	Deprecated: use "-classifications ..." instead.
-r Only outputs cumulative margin distribution.
-z [class name]
	Only outputs the source representation of the classifier,
	giving it the supplied name.
-g Only outputs the graph representation of the classifier.
-xml filename | xml-string
	Retrieves the options from the XML-data instead of the command line.
-threshold-file [file]
	The file to save the threshold data to.
	The format is determined by the extensions, e.g., '.arff' for ARFF 
	format or '.csv' for CSV.
-threshold-label [label]
	The class label to determine the threshold data for
	(default is the first label)