27 lines
1.4 KiB
Plaintext
27 lines
1.4 KiB
Plaintext
Documentation with sphinx
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Add quantification_report (akin to classification_report from sklearn) (?)
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Add NAE, NRAE
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Add "measures for evaluating ordinal"?
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Document methods with paper references
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The parallel training in svmperf seems not to work (not sure...)
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In binary quantification (hp, kindle, imdb) we used F1 in the minority class (which in kindle and hp happens to be the
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negative class). This is not covered in this new implementation, in which the binary case is not treated as such, but as
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an instance of single-label with 2 labels. Check
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Add classnames to LabelledCollection ?
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Check the overhead in OneVsAll for SVMperf-based (?)
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Add HDy to QuaNet? if so, wrap HDy into OneVsAll in case the dataset is not binary.
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Plots (one for binary -- the "diagonal", or for a specific class), another for the error as a funcition of drift.
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Add datasets for topic.
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Add other methods
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Clarify whether QuaNet is an aggregative method or not.
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Add datasets from Pérez-Gallego et al. 2017, 2019
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Add ensemble models from Pérez-Gallego et al. 2017, 2019
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Add plots models like those in Pérez-Gallego et al. 2017 (error boxes)
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Add support for CV prediction in ACC and PACC for tpr, fpr
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Add medium swap method
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Explore the hyperparameter "number of bins" in HDy
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Implement HDy for single-label?
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Rename EMQ to SLD ?
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How many times is the system of equations for ACC and PACC not solved? How many times is it clipped? Do they sum up
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to one always?
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Parallelize the kFCV in ACC and PACC |