https://github.com/foxriver76/master-thesis-rslvq

An Robust Soft Learning Vector Quantization for the scikit-multiflow streaming data framework
https://github.com/foxriver76/master-thesis-rslvq
Last synced: 8 months ago
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An Robust Soft Learning Vector Quantization for the scikit-multiflow streaming data framework
Host: GitHub
URL: https://github.com/foxriver76/master-thesis-rslvq
Owner: foxriver76
Created: 2018-07-02T10:08:16.000Z (almost 8 years ago)
Default Branch: master
Last Pushed: 2018-10-15T08:28:52.000Z (over 7 years ago)
Last Synced: 2025-01-04T17:46:03.609Z (over 1 year ago)
Language: Python
Size: 766 KB
Stars: 0
Watchers: 3
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
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README

          # multiflow-rslvq

An implementation of the Robust Soft Learning Vector Quantizatin, which works with the scikit-multiflow streaming data framework.

## Information on Concept Drift

Width indicates the width of a gradual drift. So if width is bigger than 1, the drift is gradual

otherwise abrupt. E. g. if width is set to 1000 the old and the new streams are mixed for 1000

instances. The chance of getting the old stream is determiend by a sigmoid function.

## Known Issues

The following issues could be recognized:

   - At the moment --> Everything seems to work well :-)

   

## Overview of stream generators

|Dataset|Drift Rate|

|---|---|

|[AGRAWAL](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.agrawal_generator.html#module-skmultiflow.data.agrawal_generator)|?|

|[Hyper Plane](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.hyper_plane_generator.html#module-skmultiflow.data.hyper_plane_generator)|incremental|

|[LED Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.led_generator.html#module-skmultiflow.data.led_generator)|None|

|[LED Generator Drift](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.led_generator_drift.html#module-skmultiflow.data.led_generator_drift)|?|

|[Mixed Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.mixed_generator.html#module-skmultiflow.data.mixed_generator)|Abrupt|

|[Random RBF](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.random_rbf_generator.html#module-skmultiflow.data.random_rbf_generator)|None|

|[Random RBF Drift](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.random_rbf_generator_drift.html#module-skmultiflow.data.random_rbf_generator_drift)|?|

|[Random Tree Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.random_tree_generator.html#module-skmultiflow.data.random_tree_generator)|?|

|[SEA Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.sea_generator.html#module-skmultiflow.data.sea_generator)|Abrupt| 

|[Sine Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.sine_generator.html#module-skmultiflow.data.sine_generator)|Abrupt|   

|[Data Stagger Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.stagger_generator.html#module-skmultiflow.data.stagger_generator)|Abrupt|

|[Waveform Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.waveform_generator.html#module-skmultiflow.data.waveform_generator)|None|

|[Multilabel Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.multilabel_generator.html#module-skmultiflow.data.multilabel_generator)|None|

|[Data Regression](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.regression_generator.html#module-skmultiflow.data.regression_generator)|None|

## To-Dos

Absolutley nuttin   

   

## Evaluation Tables

### Immediate Accuracy

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|99.9|67.2|99.6|99.9|**100**|**100**|**100**|

|LED G|99.9|67.1|99.8|**100**|**100**|**100**|99.9|

|SEA A|**90.0**|82.9|88.7|89.9|71.6|**90.0**|83.9|

|SEA G|**89.9**|82.2|88.9|**89.9**|67.7|89.6|83.2|

|AGR A|51.2|50.1|54.3|51.5|50.8|**99.9**|79.8|

|AGR G|53.6|52.7|53.3|53.3|55.5|**86.7**|79.3|

|RTG  |64.8|58.8|68.5|62.3|73.1|**84.0**|60.5|

|RBF F|56.2|59.7|59.8|52.5|---|59.8|**68.8**|

|RBF M|62.1|53.8|57.6|59.5|---|68.1|**74.4**|

|HYPER|84.1|56.7|**87.3**|86.1|73.6|80.3|84.9|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|75.2|63.1|75.8|74.5|74.0|**85.8**|81.5|

|Synthetic Avg Rank|3.6|6.4|4.0|3.6|4.1|**1.8**|2.7|

|---|---|---|---|---|---|---|---|

|ELEC|85.3|85.3|85.3|85.3|58.0|80.9|**88.3**|

|GMSC|86.5|71.5|93.1|85.8|14.8|**93.2**|88.1|

|POKR|73.4|74.7|**75.1**|74.8|38.9|71.2|71.3|

|---|---|---|---|---|---|---|---|

|Real Avg|81.7|77.2|**84.5**|82.0|37.2|81.8|82.6|

|Real Avg Rank|3.3|3.7|**1.7**|3.0|7.0|4.3|3.0|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|76.7|66.4|77.8|76.2|64.0|**84.9**|81.7|

|Overall Avg Rank|3.5|5.8|3.5|3.5|5.7|**2.4**|2.8|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|4|7|6|4|1|1|1|

|LED G|4|7|6|1|1|1|4|

|SEA A|1|6|4|3|7|1|5|

|SEA G|1|6|4|1|7|3|5|

|AGR A|5|7|3|4|6|1|2|

|AGR G|4|7|5|5|3|1|2|

|RTG  |5|7|4|6|2|1|3|

|RBF F|5|4|2|6|-|2|1|

|RBF M|3|6|5|4|-|2|1|

|HYPER|4|7|1|2|6|5|3|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|3.6|6.4|4.0|3.6|4.1|1.8|2.7|

|---|---|---|---|---|---|---|---|

|ELEC|2|2|2|2|7|6|1|

|GMSC|4|6|2|5|7|1|3|

|POKR|4|3|1|2|7|6|5|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|3.3|3.7|1.7|3.0|7.0|4.3|3.0|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.5|5.8|3.5|3.5|5.7|2.4|2.8|

### Immediate Kappa

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|99.9|63.5|99.6|99.9|**100**|**100**|99.9|

|LED G|99.8|63.4|99.8|**100**|**100**|**100**|99.9|

|SEA A|75.5|59.0|72.6|75.1|29.9|**75.6**|60.7|

|SEA G|**78.9**|62.8|76.8|78.8|30.5|78.2|64.9|

|AGR A|0.1|0.3|-0.1|1.4|0.3|**99.9**|58.6|

|AGR G|6.4|4.1|5.9|6.0|10.6|**73.3**|57.6|

|RTG  |26.4|17.3|31.5|23.8|36.2|**66.0**|20.7|

|RBF F|0.1|15.6|15.4|4.4|---|13.0|**24.1**|

|RBF M|7.7|6.3|14.0|17.0|---|35.9|**43.2**|

|HYPER|68.2|13.5|**74.6**|72.2|47.1|60.6|69.8|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|46.3|30.6|49.0|47.9|44.3|**70.3**|59.9|

|Synthetic Avg Rank|4.1|5.9|4.4|3.3|4.0|**2.0**|2.8|

|---|---|---|---|---|---|---|---|

|ELEC|70.0|70.0|70.0|70.0|6.3|60.8|**76.0**|

|GMSC|0.2|-0.4|0.0|-1.1|0.5|**19.3**|1.2|

|POKR|53.5|55.0|**56.2**|55.3|6.1|47.5|49.0|

|---|---|---|---|---|---|---|---|

|Real Avg|41.2|41.5|42.1|41.4|4.3|**42.5**|42.1|

|Real Avg Rank|3.3|4.0|**2.7**|3.3|5.7|4.3|**2.7**|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|45.1|33.1|47.4|46.4|33.4|**63.9**|55.8|

|Overall Avg Rank|3.9|5.5|4|3.3|4.5|**2.5**|2.8|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|3|7|6|3|1|1|3|

|LED G|5|7|5|1|1|1|4|

|SEA A|2|6|4|3|7|1|5|

|SEA G|1|6|4|2|7|3|5|

|AGR A|6|4|7|3|4|1|2|

|AGR G|4|7|6|5|3|1|2|

|RTG  |5|7|4|6|3|1|2|

|RBF F|6|2|3|5|---|4|1|

|RBF M|5|6|4|3|---|2|1|

|HYPER|4|7|1|2|6|5|3|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|4.1|5.9|4.4|3.3|4.0|2.0|2.8|

|---|---|---|---|---|---|---|---|

|ELEC|2|2|2|2|7|6|1|

|GMSC|4|7|5|6|3|1|2|

|POKR|4|3|1|2|7|6|5|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|3.3|4.0|2.7|3.3|5.7|4.3|2.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.9|5.5|4|3.3|4.5|2.5|2.8|

### Immediate Kappa T

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|99.9|63.5|99.6|99.9|**100**|**100**|99.9|

|LED G|99.8|63.4|99.8|**100**|**100**|**100**|99.9|

|SEA A|**76.4**|59.6|73.3|76.0|33.0|76.3|61.9|

|SEA G|**79.0**|62.8|76.8|78.8|32.5|78.4|65.0|

|AGR A|-0.9|-3.3|5.4|-0.3|-1.8|**99.9**|58.2|

|AGR G|0.4|-1.5|-0.1|-0.1|4.6|**71.5**|57.2|

|RTG  |27.6|17.6|34.1|24.2|41.1|**66.3**|20.5|

|RBF F|11.0|17.7|17.8|5.1|---|17.6|**30.3**|

|RBF M|20.0|5.9|14.5|18.2|---|35.9|**45.4**|

|HYPER|68.2|13.6|**74.6**|72.2|47.1|60.6|69.8|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|48.1|29.9|49.6|47.4|44.6|**70.7**|60.8|

|Synthetic Avg Rank|3.5|6.3|3.8|3.5|4.1|**2.1**|3.2|

|---|---|---|---|---|---|---|---|

|ELEC|0.0|0.0|0.0|0.0|-186.3|-30.4|**20.0**|

|GMSC|-0.5|-121.1|46.0|-10.3|-561.2|**47.1**|7.0|

|POKR|-4.3|0.6|**2.3**|0.9|-139.9|-13.0|-12.6|

|---|---|---|---|---|---|---|---|

|Real Avg|-1.6|-40.2|**16.1**|-3.1|-289.8|1.2|4.8|

|Real Avg Rank|3.3|3.7|**1.7**|3.0|7.0|4.3|3.0|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|36.7|13.8|41.9|35.7|-48.3|**54.6**|47.9|

|Overall Avg Rank|3.5|5.7|3.3|3.4|4.9|**2.6**|3.2|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|3|7|6|3|1|1|3|

|LED G|5|7|5|1|1|1|4|

|SEA A|1|6|4|3|7|2|5|

|SEA G|1|6|4|2|7|3|5|

|AGR A|5|7|3|4|6|1|2|

|AGR G|4|7|5|5|3|1|2|

|RTG  |4|7|3|5|2|1|6|

|RBF F|5|3|2|6|---|4|1|

|RBF M|3|6|5|4|---|2|1|

|HYPER|4|7|1|2|6|5|3|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|3.5|6.3|3.8|3.5|4.1|2.1|3.2|

|---|---|---|---|---|---|---|---|

|ELEC|2|2|2|2|7|6|1|

|GMSC|4|6|2|5|7|1|3|

|POKR|4|3|1|2|7|6|5|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|3.3|3.7|1.7|3.0|7.0|4.3|3.0|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.5|5.7|3.3|3.4|4.9|2.6|3.2|

### Immediate Kappa M

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|99.9|63.5|99.6|99.9|**100**|**100**|99.9|

|LED G|99.8|63.4|99.8|**100**|**100**|**100**|99.9|

|SEA A|**85.6**|75.4|83.7|85.4|59.2|85.5|76.8|

|SEA G|**83.1**|70.1|81.3|83.0|45.7|82.6|71.9|

|AGR A|-13.5|-16.2|-6.0|-12.8|-14.1|**99.9**|52.9|

|AGR G|-1.6|-3.5|-2.1|-2.2|2.6|**71.0**|51.8|

|RTG  |39.9|14.2|48.0|18.5|24.1|**58.6**|15.5|

|RBF F|0.00|5.7|6.1|7.6|---|**30.8**|7.9|

|RBF M|1.6|-6.0|7.2|11.5|---|32.4|**59.3**|

|HYPER|68.1|13.4|**74.6**|72.2|47.0|60.5|69.8|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|46.3|28.0|49.2|46.3|45.6|**72.1**|60.6|

|Synthetic Avg Rank|3.7|6.5|3.8|3.2|4.4|**1.8**|3.3|

|---|---|---|---|---|---|---|---|

|ELEC|65.4|65.4|65.4|65.4|1.0|54.9|**72.3**|

|GMSC|-94.6|-309.8|0|-104.4|-1125.7|**2.0**|-72.6|

|POKR|72.5|73.8|**74.2**|73.8|36.7|52.6|70.3|

|---|---|---|---|---|---|---|---|

|Real Avg|14.4|-56.9|**46.5**|11.6|-362.7|36.5|23.3|

|Real Avg Rank|3.3|3.3|**1.7**|3.0|7.0|4.3|3.0|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|38.9|8.4|48.6|38.3|-65.8|**63.9**|52.0|

|Overall Avg Rank|3.6|5.8|3.3|3.2|5.1|**2.4**|3.2|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|3|7|6|3|1|1|3|

|LED G|5|7|5|1|1|1|4|

|SEA A|1|6|4|3|7|2|5|

|SEA G|1|6|4|2|7|3|5|

|AGR A|5|7|3|4|6|1|2|

|AGR G|4|7|5|6|3|1|2|

|RTG  |3|7|2|5|4|1|6|

|RBF F|6|5|4|3|---|1|2|

|RBF M|5|6|4|3|---|2|1|

|HYPER|4|7|1|2|6|5|3|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|3.7|6.5|3.8|3.2|4.4|1.8|3.3|

|---|---|---|---|---|---|---|---|

|ELEC|2|2|2|2|7|6|1|

|GMSC|4|6|2|5|7|1|3|

|POKR|4|2|1|2|7|6|5|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|3.3|3.3|1.7|3.0|7.0|4.3|3.0|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.6|5.8|3.3|3.2|5.1|2.4|3.2|

### Immediate CPU-Time

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|1851.961|1645.471|1820.586|1711.530|678.343|**372.769**|770.533|

|LED G|1993.335|1577.543|1783.463|1713.072|633.197|**390.222**|846.303|

|SEA A|761.711|871.610|673.142|655.546|467.963|**208.932**|336.949|

|SEA G|724.383|898.286|659.586|672.898|439.970|**208.876**|326.061|

|AGR A|877.548|784.518|1751.439|791.685|553.756|**398.257**|563.763|

|AGR G|843.703|832.535|815.114|821.120|597.256|**381.478**|619.775|

|RTG  |780.070|662.155|685.154|694.892|489.937|**294.316**|493.638|

|RBF F|1372.500|1477.024|1450.661|1359.879|---|949.117|1047.347|

|RBF M|1369.070|1218.254|1319.601|1260.614|---|**967.928**|1113.365|

|HYPER|917.015|688.266|733.378|736.123|452.480|**287.279**|504.931|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|1149.1|1065.6|1169.2|1041.7|539.1|**445.9**|662.3|

|Synthetic Avg Rank|6.3|4.9|5.2|4.8|2.3|**1.0**|2.6|

|---|---|---|---|---|---|---|---|

|ELEC|31.085|156.332|28.727|29.116|18.302|**11.059**|14.859|

|GMSC|82.105|72.103|82.454|75.308|48.292|**15.062**|32.658|

|POKR|1602.605|1543.254|1498.409|1530.084|**446.357**|882.931|986.171|

|---|---|---|---|---|---|---|---|

|Real Avg|571.9|590.6|536.5|544.8|**171.0**|303.0|344.6|

|Real Avg Rank|6.0|6.0|5.0|5.0|2.3|**1.3**|2.3|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|1015.9|956.0|1023.2|927.1|438.7|**412.9**|589.0|

|Overall Avg Rank|6.2|5.2|5.2|4.8|2.3|**1.1**|2.5|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|7|4|6|5|2|1|3|

|LED G|7|4|6|5|2|1|3|

|SEA A|6|7|5|4|3|1|2|

|SEA G|6|7|4|5|3|1|2|

|AGR A|6|4|7|5|2|1|3|

|AGR G|7|6|4|5|2|1|3|

|RTG  |7|4|5|6|2|1|3|

|RBF F|4|6|5|3|---|1|2|

|RBF M|6|3|5|4|---|1|2|

|HYPER|7|4|5|6|2|1|3|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|6.3|4.9|5.2|4.8|2.3|1.0|2.6|

|---|---|---|---|---|---|---|---|

|ELEC|6|7|4|5|3|1|2|

|GMSC|6|4|7|5|3|1|2|

|POKR|6|7|4|5|1|2|3|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|6.0|6.0|5.0|5.0|2.3|1.3|2.3|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|6.2|5.2|5.2|4.8|2.3|1.1|2.5|

### Delayed Accuracy

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|**100**|66.1|99.8|**100**|**100**|**100**|**100**|

|LED G|**100**|63.7|**100**|**100**|**100**|**100**|99.6|

|SEA A|**90.2**|81.8|87.7|90.0|71.6|89.9|83.6|

|SEA G|**89.9**|81.5|88.5|89.7|67.6|89.7|82.9|

|AGR A|52.2|50.3|54.1|49.7|51.3|**98.8**|78.3|

|AGR G|53.5|53.4|51.5|53.6|55.7|**85.8**|77.9|

|RTG  |64.7|56.1|68.2|60.7|67.1|**94.0**|65.2|

|RBF F|57.7|50.9|50.3|**63.7**|---|50.1|53.4|

|RBF M|56.3|52.7|55.8|58.0|---|62.3|**64.6**|

|HYPER|50.3|50.1|49.5|50.4|49.6|**50.5**|49.8|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|71.5|60.7|70.5|71.6|70.4|**82.1**|75.5|

|Synthetic Avg Rank|2.7|5.9|4.4|2.9|4.1|**1.9**|3.4|

|---|---|---|---|---|---|---|---|

|ELEC|51.7|51.7|57.6|51.7|51.9|58.1|**74.5**|

|GMSC|78.7|77.0|92.9|89.1|12.4|**93.1**|78.7|

|POKR|49.9|49.9|48.1|50.8|40.5|**61.2**|52.6|

|---|---|---|---|---|---|---|---|

|Real Avg|60.1|59.5|66.2|63.9|34.9|**70.8**|68.6|

|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|**1.3**|2.3|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|68.9|60.4|69.5|69.8|60.7|**79.5**|73.9|

|Overall Avg Rank|3.1|5.7|4.2|3.1|4.6|**1.8**|3.2|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|1|7|6|1|1|1|1|

|LED G|1|7|1|1|1|1|6|

|SEA A|1|6|4|2|7|3|5|

|SEA G|1|6|4|2|7|2|5|

|AGR A|4|6|3|7|5|1|2|

|AGR G|5|6|7|4|3|1|2|

|RTG  |5|7|2|6|3|1|4|

|RBF F|2|4|5|1|---|6|3|

|RBF M|4|6|5|3|---|2|1|

|HYPER|3|4|7|2|6|1|5|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|2.7|5.9|4.4|2.9|4.1|1.9|3.4|

|---|---|---|---|---|---|---|---|

|ELEC|5|5|3|5|4|2|1|

|GMSC|4|6|2|3|7|1|4|

|POKR|4|4|6|3|7|1|2|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|1.3|2.3|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.1|5.7|4.2|3.1|4.6|1.8|3.2|

### Delayed Kappa

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|**100**|62.4|99.8|**100**|**100**|**100**|**100**|

|LED G|**100**|59.6|**100**|**100**|**100**|**100**|99.6|

|SEA A|**75.9**|56.8|70.6|75.4|29.8|75.4|60.0|

|SEA G|**78.9**|61.4|75.9|78.5|30.5|78.4|64.3|

|AGR A|0.2|1.1|-0.2|-0.2|-0.1|**97.5**|55.6|

|AGR G|7.5|6.2|3.6|6.3|10.8|**71.6**|54.8|

|RTG  |26.7|6.1|35.2|17.7|31.2|**87.4**|29.0|

|RBF F|-0.2|1.7|0.2|0.0|---|-0.3|**18.5**|

|RBF M|12.5|4.4|11.3|12.9|---|3.9|**28.9**|

|HYPER|0.6|**1.2**|-0.7|0.7|-0.5|0.1|-0.1|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|40.2|26.1|39.6|39.1|37.7|**61.4**|51.1|

|Synthetic Avg Rank|2.8|5.0|4.4|3.1|4.1|**2.6**|3.2|

|---|---|---|---|---|---|---|---|

|ELEC|3.4|3.4|0.0|3.4|3.3|18.2|**45.9**|

|GMSC|0.5|0.1|0.0|-1.9|0.3|**20.3**|0.9|

|POKR|9.3|9.3|7.6|10.0|2.1|**28.2**|13.6|

|---|---|---|---|---|---|---|---|

|Real Avg|4.4|4.3|2.5|3.8|1.9|**22.2**|20.1|

|Real Avg Rank|3.3|4.0|6.3|4.3|5.7|**1.3**|1.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|31.9|21.1|31.0|31.0|27.9|**52.4**|43.9|

|Overall Avg Rank|2.9|4.8|4.8|3.4|4.5|**2.3**|2.8|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|1|7|6|1|1|1|1|

|LED G|1|7|1|1|1|1|6|

|SEA A|1|6|4|2|7|2|5|

|SEA G|1|6|4|2|7|3|5|

|AGR A|4|3|6|6|5|1|2|

|AGR G|4|6|7|5|3|1|2|

|RTG  |5|7|2|6|3|1|4|

|RBF F|5|2|3|4|---|6|1|

|RBF M|3|5|4|2|---|6|1|

|HYPER|3|1|7|2|6|4|5|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|2.8|5.0|4.4|3.1|4.1|2.6|3.2|

|---|---|---|---|---|---|---|---|

|ELEC|3|3|7|3|6|2|1|

|GMSC|3|5|6|7|4|1|2|

|POKR|4|4|6|3|7|1|2|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|3.3|4.0|6.3|4.3|5.7|1.3|1.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|2.9|4.8|4.8|3.4|4.5|2.3|2.8|

### Delayed Kappa T

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|**100**|62.4|99.8|**100**|**100**|**100**|**100**|

|LED G|**100**|59.7|**100**|**100**|**100**|**100**|99.6|

|SEA A|**76.7**|57.0|70.9|76.3|32.9|76.1|61.2|

|SEA G|**79.0**|61.3|75.9|78.5|32.4|78.5|64.4|

|AGR A|1.1|-2.9|5.2|-0.4|-0.8|**97.5**|55.1|

|AGR G|0.2|0.1|-4.1|0.5|4.9|**69.6**|54.3|

|RTG  |27.9|10.6|36.1|19.9|32.8|**87.4**|29.5|

|RBF F|13.3|1.7|0.4|**21.4**|---|0.0|5.1|

|RBF M|12.6|5.0|11.5|15.5|---|21.7|**28.9**|

|HYPER|-196.0|-196.6|-200.9|-195.6|-200.6|**-192.3**|-196.7|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|21.5|5.8|19.5|21.6|12.7|**43.9**|30.1|

|Synthetic Avg Rank|2.7|6.0|4.4|2.7|4.3|**1.9**|3.4|

|---|---|---|---|---|---|---|---|

|ELEC|-240.9|-240.9|-199.5|-240.9|-239.2|-195.7|**-79.9**|

|GMSC|-61.8|-75.0|46.1|16.9|-566.3|**47.7**|-62.1|

|POKR|-95.9|-95.9|-102.8|-92.4|-132.8|**-51.8**|-85.2|

|---|---|---|---|---|---|---|---|

|Real Avg|-132.9|-137.3|-85.4|-105.5|-312.8|**-66.6**|-75.7|

|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|**1.3**|2.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|-14.1|-27.2|-4.7|-7.7|-76.1|**18.4**|5.7|

|Overall Avg Rank|3.1|5.8|4.2|2.9|4.7|**1.8**|3.2|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|1|7|6|1|1|1|1|

|LED G|1|7|1|1|1|1|6|

|SEA A|1|6|4|2|7|3|5|

|SEA G|1|6|4|2|7|2|5|

|AGR A|4|7|3|5|6|1|2|

|AGR G|5|6|7|4|3|1|2|

|RTG  |5|7|2|6|3|1|4|

|RBF F|2|4|5|1|---|6|3|

|RBF M|4|6|5|3|---|2|1|

|HYPER|3|4|7|2|6|1|5|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|2.7|6.0|4.4|2.7|4.3|1.9|3.4|

|---|---|---|---|---|---|---|---|

|ELEC|5|5|3|5|4|2|1|

|GMSC|4|6|2|3|7|1|5|

|POKR|4|4|6|3|7|1|2|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|1.3|2.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.1|5.8|4.2|2.9|4.7|1.8|3.2|

### Delayed Kappa M

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|**100**|62.4|99.8|**100**|**100**|**100**|**100**|

|LED G|**100**|59.7|**100**|**100**|**100**|**100**|99.6|

|SEA A|**85.8**|73.9|82.3|85.6|59.2|85.4|76.4|

|SEA G|**83.1**|68.9|80.6|82.7|45.7|82.7|71.4|

|AGR A|16.0|12.6|-6.0|11.6|-12.6|**97.2**|61.8|

|AGR G|14.5|14.3|10.8|14.7|18.5|**73.9**|61.2|

|RTG  |17.6|22.7|31.1|31.2|22.6|**90.3**|22.2|

|RBF F|-0.5|2.6|-2.4|-0.1|---|**4.1**|-8.0|

|RBF M|13.8|-2.1|15.6|23.6|---|6.3|**24.7**|

|HYPER|-1.7|-12.0|8.3|-103.0|-11.7|-0.7|**11.0**|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|42.9|30.3|42.0|34.6|40.2|**63.9**|52.0|

|Synthetic Avg Rank|3.1|5.4|4.1|2.9|4.5|**1.9**|3.5|

|---|---|---|---|---|---|---|---|

|ELEC|-13.9|-13.9|0.0|-13.9|-13.3|1.2|**39.9**|

|GMSC|-200.1|-224.7|0.0|-54.1|-1136.2|**2.9**|-200.8|

|POKR|41.2|41.2|39.1|42.3|-4.1|**54.4**|44.4|

|---|---|---|---|---|---|---|---|

|Real Avg|-57.6|-65.8|13.0|-8.5|-384.5|**19.5**|-38.8|

|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|**1.3**|2.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|19.7|8.1|35.3|24.7|-75.6|**53.7**|31.1|

|Overall Avg Rank|3.4|5.3|4|3.1|4.9|**1.8**|3.3|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|1|7|6|1|1|1|1|

|LED G|1|7|1|1|1|1|6|

|SEA A|1|6|4|2|7|3|5|

|SEA G|1|6|4|2|7|2|5|

|AGR A|3|4|6|5|7|1|2|

|AGR G|5|6|7|4|3|1|2|

|RTG  |7|4|3|2|5|1|6|

|RBF F|4|2|5|3|---|1|6|

|RBF M|4|6|3|2|---|5|1|

|HYPER|4|6|2|7|5|3|1|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|3.1|5.4|4.1|2.9|4.5|1.9|3.5|

|---|---|---|---|---|---|---|---|

|ELEC|5|5|3|5|4|2|1|

|GMSC|4|6|2|3|7|1|5|

|POKR|4|4|6|3|7|1|2|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|1.3|2.7|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|3.4|5.3|4|3.1|4.9|1.8|3.3|

### Delayed CPU-Time

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|1012.091|795.131|893.665|820.796|288.025|**191.365**|373.476|

|LED G|917.185|729.234|895.148|1000.183|309.330|**187.175**|398.284|

|SEA A|269.649|346.151|250.556|255.098|209.188|**99.808**|152.553|

|SEA G|300.443|347.493|283.960|255.368|197.863|**100.626**|151.474|

|AGR A|383.949|364.802|859.119|405.709|292.374|**184.668**|349.424|

|AGR G|388.325|384.454|407.795|404.792|339.822|**237.133**|323.537|

|RTG  |316.509|273.405|292.777|294.298|233.565|**137.419**|220.481|

|RBF F|860.316|886.757|795.317|869.959|---|**689.294**|826.780|

|RBF M|858.122|833.409|785.766|894.627|---|**751.568**|814.607|

|HYPER|287.258|254.839|239.510|254.784|202.320|**123.865**|233.962|

|---|---|---|---|---|---|---|---|

|Synthetic Avg|559.4|521.6|570.4|545.6|**259.1**|270.3|384.5|

|Synthetic Avg Rank|5.8|5.0|4.7|5.5|2.5|**1.0**|2.6|

|---|---|---|---|---|---|---|---|

|ELEC|11.679|81.771|11.036|10.880|8.336|**4.550**|6.784|

|GMSC|30.089|26.620|30.008|27.415|19.984|**7.512**|17.629|

|POKR|746.798|652.104|694.198|688.450|**209.899**|458.636|618.694|

|---|---|---|---|---|---|---|---|

|Real Avg|262.9|253.5|245.1|242.2|**79.4**|156.9|214.4|

|Real Avg Rank|6.7|5.0|5.7|4.7|2.3|**1.3**|2.3|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg|491.0|459.7|495.3|475.6|**210.1**|244.1|345.2|

|Overall Avg Rank|6.0|5.0|4.9|5.3|2.5|**1.1**|2.5|

Rank Table:

|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|

|---|---|---|---|---|---|---|---|

|LED A|7|4|6|5|2|1|3|

|LED G|6|4|5|7|2|1|3|

|SEA A|6|7|4|5|3|1|2|

|SEA G|6|7|5|4|3|1|2|

|AGR A|5|4|7|6|2|1|3|

|AGR G|5|4|7|6|3|1|2|

|RTG  |7|4|5|6|3|1|2|

|RBF F|4|6|2|5|---|1|3|

|RBF M|5|4|2|6|---|1|3|

|HYPER|7|6|4|5|2|1|3|

|---|---|---|---|---|---|---|---|

|Synthetic Avg Rank|   |   |   |   |   |   |   |

|---|---|---|---|---|---|---|---|

|ELEC|6|7|5|4|3|1|2|

|GMSC|7|4|6|5|3|1|2|

|POKR|7|4|6|5|1|2|3|

|---|---|---|---|---|---|---|---|

|Real Avg Rank|6.7|5.0|5.7|4.7|2.3|1.3|2.3|

|---|---|---|---|---|---|---|---|

|---|---|---|---|---|---|---|---|

|Overall Avg Rank|6.0|5.0|4.9|5.3|2.5|1.1|2.5|
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