QuaPy/TODO.txt

Documentation with sphinx
Add quantification_report (akin to classification_report from sklearn)
Add optimization - artificial sampling
Add NAE, NRAE
Add "measures for evaluating ordinal"?
Document methods with paper references
The parallel training in svmperf seems not to work (not sure...)
svmperf wrapper added 2020-12-03 16:59:13 +01:00			`Documentation with sphinx`
evaluation by artificial prevalence sampling added. New methods added. New util functions added to quapy.functional and quapy.utils 2020-12-10 19:04:33 +01:00			`Add quantification_report (akin to classification_report from sklearn)`
			`Add optimization - artificial sampling`
			`Add NAE, NRAE`
			`Add "measures for evaluating ordinal"?`
aggregative methods adapted. Explicit loss minimization methods (SVMQ, SVMKLD, ...) added and with support to binary or single-label. HDy added 2020-12-04 19:32:08 +01:00			`Document methods with paper references`
refactoring aggregative methods as methods that not only implement 'classify' and 'quantify', but that also implement 'aggregate' and that, by default, have a default implementation of 'quantify' as a pipeline of 'classify' and 'aggregate'; this helps speeding up evaluations A LOT, since the documents can be pre-classified and the samples are carried out across pre-classified values (labels, or posterior probabilities), and thus only aggregate is called many times within the artificial sampling protocol 2020-12-11 19:28:17 +01:00			`The parallel training in svmperf seems not to work (not sure...)`
merged 2020-12-10 19:08:22 +01:00