{"id":16397410,"url":"https://github.com/foxriver76/master-thesis-rslvq","last_synced_at":"2025-10-30T00:06:23.141Z","repository":{"id":95824884,"uuid":"139425955","full_name":"foxriver76/master-thesis-rslvq","owner":"foxriver76","description":"An Robust Soft Learning Vector Quantization for the scikit-multiflow streaming data framework","archived":false,"fork":false,"pushed_at":"2018-10-15T08:28:52.000Z","size":784,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-04T17:46:03.609Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/foxriver76.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-07-02T10:08:16.000Z","updated_at":"2022-02-22T09:30:57.000Z","dependencies_parsed_at":null,"dependency_job_id":"852bd054-1d89-4222-89c3-6c42894d8366","html_url":"https://github.com/foxriver76/master-thesis-rslvq","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/foxriver76%2Fmaster-thesis-rslvq","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/foxriver76%2Fmaster-thesis-rslvq/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/foxriver76%2Fmaster-thesis-rslvq/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/foxriver76%2Fmaster-thesis-rslvq/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/foxriver76","download_url":"https://codeload.github.com/foxriver76/master-thesis-rslvq/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240286519,"owners_count":19777353,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-11T05:10:01.434Z","updated_at":"2025-10-30T00:06:18.073Z","avatar_url":"https://github.com/foxriver76.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# multiflow-rslvq\nAn implementation of the Robust Soft Learning Vector Quantizatin, which works with the scikit-multiflow streaming data framework.\n\n## Information on Concept Drift\nWidth indicates the width of a gradual drift. So if width is bigger than 1, the drift is gradual\notherwise abrupt. E. g. if width is set to 1000 the old and the new streams are mixed for 1000\ninstances. The chance of getting the old stream is determiend by a sigmoid function.\n\n## Known Issues\nThe following issues could be recognized:\n\n   - At the moment --\u003e Everything seems to work well :-)\n   \n## Overview of stream generators\n\n|Dataset|Drift Rate|\n|---|---|\n|[AGRAWAL](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.agrawal_generator.html#module-skmultiflow.data.agrawal_generator)|?|\n|[Hyper Plane](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.hyper_plane_generator.html#module-skmultiflow.data.hyper_plane_generator)|incremental|\n|[LED Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.led_generator.html#module-skmultiflow.data.led_generator)|None|\n|[LED Generator Drift](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.led_generator_drift.html#module-skmultiflow.data.led_generator_drift)|?|\n|[Mixed Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.mixed_generator.html#module-skmultiflow.data.mixed_generator)|Abrupt|\n|[Random RBF](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.random_rbf_generator.html#module-skmultiflow.data.random_rbf_generator)|None|\n|[Random RBF Drift](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.random_rbf_generator_drift.html#module-skmultiflow.data.random_rbf_generator_drift)|?|\n|[Random Tree Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.random_tree_generator.html#module-skmultiflow.data.random_tree_generator)|?|\n|[SEA Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.sea_generator.html#module-skmultiflow.data.sea_generator)|Abrupt| \n|[Sine Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.sine_generator.html#module-skmultiflow.data.sine_generator)|Abrupt|   \n|[Data Stagger Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.stagger_generator.html#module-skmultiflow.data.stagger_generator)|Abrupt|\n|[Waveform Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.waveform_generator.html#module-skmultiflow.data.waveform_generator)|None|\n|[Multilabel Generator](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.multilabel_generator.html#module-skmultiflow.data.multilabel_generator)|None|\n|[Data Regression](https://scikit-multiflow.github.io/scikit-multiflow/skmultiflow.data.regression_generator.html#module-skmultiflow.data.regression_generator)|None|\n\n## To-Dos\n\nAbsolutley nuttin   \n   \n## Evaluation Tables\n\n### Immediate Accuracy\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|99.9|67.2|99.6|99.9|**100**|**100**|**100**|\n|LED G|99.9|67.1|99.8|**100**|**100**|**100**|99.9|\n|SEA A|**90.0**|82.9|88.7|89.9|71.6|**90.0**|83.9|\n|SEA G|**89.9**|82.2|88.9|**89.9**|67.7|89.6|83.2|\n|AGR A|51.2|50.1|54.3|51.5|50.8|**99.9**|79.8|\n|AGR G|53.6|52.7|53.3|53.3|55.5|**86.7**|79.3|\n|RTG  |64.8|58.8|68.5|62.3|73.1|**84.0**|60.5|\n|RBF F|56.2|59.7|59.8|52.5|---|59.8|**68.8**|\n|RBF M|62.1|53.8|57.6|59.5|---|68.1|**74.4**|\n|HYPER|84.1|56.7|**87.3**|86.1|73.6|80.3|84.9|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|75.2|63.1|75.8|74.5|74.0|**85.8**|81.5|\n|Synthetic Avg Rank|3.6|6.4|4.0|3.6|4.1|**1.8**|2.7|\n|---|---|---|---|---|---|---|---|\n|ELEC|85.3|85.3|85.3|85.3|58.0|80.9|**88.3**|\n|GMSC|86.5|71.5|93.1|85.8|14.8|**93.2**|88.1|\n|POKR|73.4|74.7|**75.1**|74.8|38.9|71.2|71.3|\n|---|---|---|---|---|---|---|---|\n|Real Avg|81.7|77.2|**84.5**|82.0|37.2|81.8|82.6|\n|Real Avg Rank|3.3|3.7|**1.7**|3.0|7.0|4.3|3.0|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|76.7|66.4|77.8|76.2|64.0|**84.9**|81.7|\n|Overall Avg Rank|3.5|5.8|3.5|3.5|5.7|**2.4**|2.8|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|4|7|6|4|1|1|1|\n|LED G|4|7|6|1|1|1|4|\n|SEA A|1|6|4|3|7|1|5|\n|SEA G|1|6|4|1|7|3|5|\n|AGR A|5|7|3|4|6|1|2|\n|AGR G|4|7|5|5|3|1|2|\n|RTG  |5|7|4|6|2|1|3|\n|RBF F|5|4|2|6|-|2|1|\n|RBF M|3|6|5|4|-|2|1|\n|HYPER|4|7|1|2|6|5|3|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|3.6|6.4|4.0|3.6|4.1|1.8|2.7|\n|---|---|---|---|---|---|---|---|\n|ELEC|2|2|2|2|7|6|1|\n|GMSC|4|6|2|5|7|1|3|\n|POKR|4|3|1|2|7|6|5|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|3.3|3.7|1.7|3.0|7.0|4.3|3.0|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.5|5.8|3.5|3.5|5.7|2.4|2.8|\n\n### Immediate Kappa\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|99.9|63.5|99.6|99.9|**100**|**100**|99.9|\n|LED G|99.8|63.4|99.8|**100**|**100**|**100**|99.9|\n|SEA A|75.5|59.0|72.6|75.1|29.9|**75.6**|60.7|\n|SEA G|**78.9**|62.8|76.8|78.8|30.5|78.2|64.9|\n|AGR A|0.1|0.3|-0.1|1.4|0.3|**99.9**|58.6|\n|AGR G|6.4|4.1|5.9|6.0|10.6|**73.3**|57.6|\n|RTG  |26.4|17.3|31.5|23.8|36.2|**66.0**|20.7|\n|RBF F|0.1|15.6|15.4|4.4|---|13.0|**24.1**|\n|RBF M|7.7|6.3|14.0|17.0|---|35.9|**43.2**|\n|HYPER|68.2|13.5|**74.6**|72.2|47.1|60.6|69.8|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|46.3|30.6|49.0|47.9|44.3|**70.3**|59.9|\n|Synthetic Avg Rank|4.1|5.9|4.4|3.3|4.0|**2.0**|2.8|\n|---|---|---|---|---|---|---|---|\n|ELEC|70.0|70.0|70.0|70.0|6.3|60.8|**76.0**|\n|GMSC|0.2|-0.4|0.0|-1.1|0.5|**19.3**|1.2|\n|POKR|53.5|55.0|**56.2**|55.3|6.1|47.5|49.0|\n|---|---|---|---|---|---|---|---|\n|Real Avg|41.2|41.5|42.1|41.4|4.3|**42.5**|42.1|\n|Real Avg Rank|3.3|4.0|**2.7**|3.3|5.7|4.3|**2.7**|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|45.1|33.1|47.4|46.4|33.4|**63.9**|55.8|\n|Overall Avg Rank|3.9|5.5|4|3.3|4.5|**2.5**|2.8|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|3|7|6|3|1|1|3|\n|LED G|5|7|5|1|1|1|4|\n|SEA A|2|6|4|3|7|1|5|\n|SEA G|1|6|4|2|7|3|5|\n|AGR A|6|4|7|3|4|1|2|\n|AGR G|4|7|6|5|3|1|2|\n|RTG  |5|7|4|6|3|1|2|\n|RBF F|6|2|3|5|---|4|1|\n|RBF M|5|6|4|3|---|2|1|\n|HYPER|4|7|1|2|6|5|3|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|4.1|5.9|4.4|3.3|4.0|2.0|2.8|\n|---|---|---|---|---|---|---|---|\n|ELEC|2|2|2|2|7|6|1|\n|GMSC|4|7|5|6|3|1|2|\n|POKR|4|3|1|2|7|6|5|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|3.3|4.0|2.7|3.3|5.7|4.3|2.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.9|5.5|4|3.3|4.5|2.5|2.8|\n\n\n### Immediate Kappa T\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|99.9|63.5|99.6|99.9|**100**|**100**|99.9|\n|LED G|99.8|63.4|99.8|**100**|**100**|**100**|99.9|\n|SEA A|**76.4**|59.6|73.3|76.0|33.0|76.3|61.9|\n|SEA G|**79.0**|62.8|76.8|78.8|32.5|78.4|65.0|\n|AGR A|-0.9|-3.3|5.4|-0.3|-1.8|**99.9**|58.2|\n|AGR G|0.4|-1.5|-0.1|-0.1|4.6|**71.5**|57.2|\n|RTG  |27.6|17.6|34.1|24.2|41.1|**66.3**|20.5|\n|RBF F|11.0|17.7|17.8|5.1|---|17.6|**30.3**|\n|RBF M|20.0|5.9|14.5|18.2|---|35.9|**45.4**|\n|HYPER|68.2|13.6|**74.6**|72.2|47.1|60.6|69.8|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|48.1|29.9|49.6|47.4|44.6|**70.7**|60.8|\n|Synthetic Avg Rank|3.5|6.3|3.8|3.5|4.1|**2.1**|3.2|\n|---|---|---|---|---|---|---|---|\n|ELEC|0.0|0.0|0.0|0.0|-186.3|-30.4|**20.0**|\n|GMSC|-0.5|-121.1|46.0|-10.3|-561.2|**47.1**|7.0|\n|POKR|-4.3|0.6|**2.3**|0.9|-139.9|-13.0|-12.6|\n|---|---|---|---|---|---|---|---|\n|Real Avg|-1.6|-40.2|**16.1**|-3.1|-289.8|1.2|4.8|\n|Real Avg Rank|3.3|3.7|**1.7**|3.0|7.0|4.3|3.0|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|36.7|13.8|41.9|35.7|-48.3|**54.6**|47.9|\n|Overall Avg Rank|3.5|5.7|3.3|3.4|4.9|**2.6**|3.2|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|3|7|6|3|1|1|3|\n|LED G|5|7|5|1|1|1|4|\n|SEA A|1|6|4|3|7|2|5|\n|SEA G|1|6|4|2|7|3|5|\n|AGR A|5|7|3|4|6|1|2|\n|AGR G|4|7|5|5|3|1|2|\n|RTG  |4|7|3|5|2|1|6|\n|RBF F|5|3|2|6|---|4|1|\n|RBF M|3|6|5|4|---|2|1|\n|HYPER|4|7|1|2|6|5|3|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|3.5|6.3|3.8|3.5|4.1|2.1|3.2|\n|---|---|---|---|---|---|---|---|\n|ELEC|2|2|2|2|7|6|1|\n|GMSC|4|6|2|5|7|1|3|\n|POKR|4|3|1|2|7|6|5|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|3.3|3.7|1.7|3.0|7.0|4.3|3.0|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.5|5.7|3.3|3.4|4.9|2.6|3.2|\n\n### Immediate Kappa M\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|99.9|63.5|99.6|99.9|**100**|**100**|99.9|\n|LED G|99.8|63.4|99.8|**100**|**100**|**100**|99.9|\n|SEA A|**85.6**|75.4|83.7|85.4|59.2|85.5|76.8|\n|SEA G|**83.1**|70.1|81.3|83.0|45.7|82.6|71.9|\n|AGR A|-13.5|-16.2|-6.0|-12.8|-14.1|**99.9**|52.9|\n|AGR G|-1.6|-3.5|-2.1|-2.2|2.6|**71.0**|51.8|\n|RTG  |39.9|14.2|48.0|18.5|24.1|**58.6**|15.5|\n|RBF F|0.00|5.7|6.1|7.6|---|**30.8**|7.9|\n|RBF M|1.6|-6.0|7.2|11.5|---|32.4|**59.3**|\n|HYPER|68.1|13.4|**74.6**|72.2|47.0|60.5|69.8|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|46.3|28.0|49.2|46.3|45.6|**72.1**|60.6|\n|Synthetic Avg Rank|3.7|6.5|3.8|3.2|4.4|**1.8**|3.3|\n|---|---|---|---|---|---|---|---|\n|ELEC|65.4|65.4|65.4|65.4|1.0|54.9|**72.3**|\n|GMSC|-94.6|-309.8|0|-104.4|-1125.7|**2.0**|-72.6|\n|POKR|72.5|73.8|**74.2**|73.8|36.7|52.6|70.3|\n|---|---|---|---|---|---|---|---|\n|Real Avg|14.4|-56.9|**46.5**|11.6|-362.7|36.5|23.3|\n|Real Avg Rank|3.3|3.3|**1.7**|3.0|7.0|4.3|3.0|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|38.9|8.4|48.6|38.3|-65.8|**63.9**|52.0|\n|Overall Avg Rank|3.6|5.8|3.3|3.2|5.1|**2.4**|3.2|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|3|7|6|3|1|1|3|\n|LED G|5|7|5|1|1|1|4|\n|SEA A|1|6|4|3|7|2|5|\n|SEA G|1|6|4|2|7|3|5|\n|AGR A|5|7|3|4|6|1|2|\n|AGR G|4|7|5|6|3|1|2|\n|RTG  |3|7|2|5|4|1|6|\n|RBF F|6|5|4|3|---|1|2|\n|RBF M|5|6|4|3|---|2|1|\n|HYPER|4|7|1|2|6|5|3|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|3.7|6.5|3.8|3.2|4.4|1.8|3.3|\n|---|---|---|---|---|---|---|---|\n|ELEC|2|2|2|2|7|6|1|\n|GMSC|4|6|2|5|7|1|3|\n|POKR|4|2|1|2|7|6|5|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|3.3|3.3|1.7|3.0|7.0|4.3|3.0|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.6|5.8|3.3|3.2|5.1|2.4|3.2|\n\n### Immediate CPU-Time\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|1851.961|1645.471|1820.586|1711.530|678.343|**372.769**|770.533|\n|LED G|1993.335|1577.543|1783.463|1713.072|633.197|**390.222**|846.303|\n|SEA A|761.711|871.610|673.142|655.546|467.963|**208.932**|336.949|\n|SEA G|724.383|898.286|659.586|672.898|439.970|**208.876**|326.061|\n|AGR A|877.548|784.518|1751.439|791.685|553.756|**398.257**|563.763|\n|AGR G|843.703|832.535|815.114|821.120|597.256|**381.478**|619.775|\n|RTG  |780.070|662.155|685.154|694.892|489.937|**294.316**|493.638|\n|RBF F|1372.500|1477.024|1450.661|1359.879|---|949.117|1047.347|\n|RBF M|1369.070|1218.254|1319.601|1260.614|---|**967.928**|1113.365|\n|HYPER|917.015|688.266|733.378|736.123|452.480|**287.279**|504.931|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|1149.1|1065.6|1169.2|1041.7|539.1|**445.9**|662.3|\n|Synthetic Avg Rank|6.3|4.9|5.2|4.8|2.3|**1.0**|2.6|\n|---|---|---|---|---|---|---|---|\n|ELEC|31.085|156.332|28.727|29.116|18.302|**11.059**|14.859|\n|GMSC|82.105|72.103|82.454|75.308|48.292|**15.062**|32.658|\n|POKR|1602.605|1543.254|1498.409|1530.084|**446.357**|882.931|986.171|\n|---|---|---|---|---|---|---|---|\n|Real Avg|571.9|590.6|536.5|544.8|**171.0**|303.0|344.6|\n|Real Avg Rank|6.0|6.0|5.0|5.0|2.3|**1.3**|2.3|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|1015.9|956.0|1023.2|927.1|438.7|**412.9**|589.0|\n|Overall Avg Rank|6.2|5.2|5.2|4.8|2.3|**1.1**|2.5|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|7|4|6|5|2|1|3|\n|LED G|7|4|6|5|2|1|3|\n|SEA A|6|7|5|4|3|1|2|\n|SEA G|6|7|4|5|3|1|2|\n|AGR A|6|4|7|5|2|1|3|\n|AGR G|7|6|4|5|2|1|3|\n|RTG  |7|4|5|6|2|1|3|\n|RBF F|4|6|5|3|---|1|2|\n|RBF M|6|3|5|4|---|1|2|\n|HYPER|7|4|5|6|2|1|3|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|6.3|4.9|5.2|4.8|2.3|1.0|2.6|\n|---|---|---|---|---|---|---|---|\n|ELEC|6|7|4|5|3|1|2|\n|GMSC|6|4|7|5|3|1|2|\n|POKR|6|7|4|5|1|2|3|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|6.0|6.0|5.0|5.0|2.3|1.3|2.3|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|6.2|5.2|5.2|4.8|2.3|1.1|2.5|\n\n### Delayed Accuracy\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|**100**|66.1|99.8|**100**|**100**|**100**|**100**|\n|LED G|**100**|63.7|**100**|**100**|**100**|**100**|99.6|\n|SEA A|**90.2**|81.8|87.7|90.0|71.6|89.9|83.6|\n|SEA G|**89.9**|81.5|88.5|89.7|67.6|89.7|82.9|\n|AGR A|52.2|50.3|54.1|49.7|51.3|**98.8**|78.3|\n|AGR G|53.5|53.4|51.5|53.6|55.7|**85.8**|77.9|\n|RTG  |64.7|56.1|68.2|60.7|67.1|**94.0**|65.2|\n|RBF F|57.7|50.9|50.3|**63.7**|---|50.1|53.4|\n|RBF M|56.3|52.7|55.8|58.0|---|62.3|**64.6**|\n|HYPER|50.3|50.1|49.5|50.4|49.6|**50.5**|49.8|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|71.5|60.7|70.5|71.6|70.4|**82.1**|75.5|\n|Synthetic Avg Rank|2.7|5.9|4.4|2.9|4.1|**1.9**|3.4|\n|---|---|---|---|---|---|---|---|\n|ELEC|51.7|51.7|57.6|51.7|51.9|58.1|**74.5**|\n|GMSC|78.7|77.0|92.9|89.1|12.4|**93.1**|78.7|\n|POKR|49.9|49.9|48.1|50.8|40.5|**61.2**|52.6|\n|---|---|---|---|---|---|---|---|\n|Real Avg|60.1|59.5|66.2|63.9|34.9|**70.8**|68.6|\n|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|**1.3**|2.3|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|68.9|60.4|69.5|69.8|60.7|**79.5**|73.9|\n|Overall Avg Rank|3.1|5.7|4.2|3.1|4.6|**1.8**|3.2|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|1|7|6|1|1|1|1|\n|LED G|1|7|1|1|1|1|6|\n|SEA A|1|6|4|2|7|3|5|\n|SEA G|1|6|4|2|7|2|5|\n|AGR A|4|6|3|7|5|1|2|\n|AGR G|5|6|7|4|3|1|2|\n|RTG  |5|7|2|6|3|1|4|\n|RBF F|2|4|5|1|---|6|3|\n|RBF M|4|6|5|3|---|2|1|\n|HYPER|3|4|7|2|6|1|5|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|2.7|5.9|4.4|2.9|4.1|1.9|3.4|\n|---|---|---|---|---|---|---|---|\n|ELEC|5|5|3|5|4|2|1|\n|GMSC|4|6|2|3|7|1|4|\n|POKR|4|4|6|3|7|1|2|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|1.3|2.3|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.1|5.7|4.2|3.1|4.6|1.8|3.2|\n\n### Delayed Kappa\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|**100**|62.4|99.8|**100**|**100**|**100**|**100**|\n|LED G|**100**|59.6|**100**|**100**|**100**|**100**|99.6|\n|SEA A|**75.9**|56.8|70.6|75.4|29.8|75.4|60.0|\n|SEA G|**78.9**|61.4|75.9|78.5|30.5|78.4|64.3|\n|AGR A|0.2|1.1|-0.2|-0.2|-0.1|**97.5**|55.6|\n|AGR G|7.5|6.2|3.6|6.3|10.8|**71.6**|54.8|\n|RTG  |26.7|6.1|35.2|17.7|31.2|**87.4**|29.0|\n|RBF F|-0.2|1.7|0.2|0.0|---|-0.3|**18.5**|\n|RBF M|12.5|4.4|11.3|12.9|---|3.9|**28.9**|\n|HYPER|0.6|**1.2**|-0.7|0.7|-0.5|0.1|-0.1|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|40.2|26.1|39.6|39.1|37.7|**61.4**|51.1|\n|Synthetic Avg Rank|2.8|5.0|4.4|3.1|4.1|**2.6**|3.2|\n|---|---|---|---|---|---|---|---|\n|ELEC|3.4|3.4|0.0|3.4|3.3|18.2|**45.9**|\n|GMSC|0.5|0.1|0.0|-1.9|0.3|**20.3**|0.9|\n|POKR|9.3|9.3|7.6|10.0|2.1|**28.2**|13.6|\n|---|---|---|---|---|---|---|---|\n|Real Avg|4.4|4.3|2.5|3.8|1.9|**22.2**|20.1|\n|Real Avg Rank|3.3|4.0|6.3|4.3|5.7|**1.3**|1.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|31.9|21.1|31.0|31.0|27.9|**52.4**|43.9|\n|Overall Avg Rank|2.9|4.8|4.8|3.4|4.5|**2.3**|2.8|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|1|7|6|1|1|1|1|\n|LED G|1|7|1|1|1|1|6|\n|SEA A|1|6|4|2|7|2|5|\n|SEA G|1|6|4|2|7|3|5|\n|AGR A|4|3|6|6|5|1|2|\n|AGR G|4|6|7|5|3|1|2|\n|RTG  |5|7|2|6|3|1|4|\n|RBF F|5|2|3|4|---|6|1|\n|RBF M|3|5|4|2|---|6|1|\n|HYPER|3|1|7|2|6|4|5|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|2.8|5.0|4.4|3.1|4.1|2.6|3.2|\n|---|---|---|---|---|---|---|---|\n|ELEC|3|3|7|3|6|2|1|\n|GMSC|3|5|6|7|4|1|2|\n|POKR|4|4|6|3|7|1|2|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|3.3|4.0|6.3|4.3|5.7|1.3|1.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|2.9|4.8|4.8|3.4|4.5|2.3|2.8|\n\n### Delayed Kappa T\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|**100**|62.4|99.8|**100**|**100**|**100**|**100**|\n|LED G|**100**|59.7|**100**|**100**|**100**|**100**|99.6|\n|SEA A|**76.7**|57.0|70.9|76.3|32.9|76.1|61.2|\n|SEA G|**79.0**|61.3|75.9|78.5|32.4|78.5|64.4|\n|AGR A|1.1|-2.9|5.2|-0.4|-0.8|**97.5**|55.1|\n|AGR G|0.2|0.1|-4.1|0.5|4.9|**69.6**|54.3|\n|RTG  |27.9|10.6|36.1|19.9|32.8|**87.4**|29.5|\n|RBF F|13.3|1.7|0.4|**21.4**|---|0.0|5.1|\n|RBF M|12.6|5.0|11.5|15.5|---|21.7|**28.9**|\n|HYPER|-196.0|-196.6|-200.9|-195.6|-200.6|**-192.3**|-196.7|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|21.5|5.8|19.5|21.6|12.7|**43.9**|30.1|\n|Synthetic Avg Rank|2.7|6.0|4.4|2.7|4.3|**1.9**|3.4|\n|---|---|---|---|---|---|---|---|\n|ELEC|-240.9|-240.9|-199.5|-240.9|-239.2|-195.7|**-79.9**|\n|GMSC|-61.8|-75.0|46.1|16.9|-566.3|**47.7**|-62.1|\n|POKR|-95.9|-95.9|-102.8|-92.4|-132.8|**-51.8**|-85.2|\n|---|---|---|---|---|---|---|---|\n|Real Avg|-132.9|-137.3|-85.4|-105.5|-312.8|**-66.6**|-75.7|\n|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|**1.3**|2.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|-14.1|-27.2|-4.7|-7.7|-76.1|**18.4**|5.7|\n|Overall Avg Rank|3.1|5.8|4.2|2.9|4.7|**1.8**|3.2|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|1|7|6|1|1|1|1|\n|LED G|1|7|1|1|1|1|6|\n|SEA A|1|6|4|2|7|3|5|\n|SEA G|1|6|4|2|7|2|5|\n|AGR A|4|7|3|5|6|1|2|\n|AGR G|5|6|7|4|3|1|2|\n|RTG  |5|7|2|6|3|1|4|\n|RBF F|2|4|5|1|---|6|3|\n|RBF M|4|6|5|3|---|2|1|\n|HYPER|3|4|7|2|6|1|5|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|2.7|6.0|4.4|2.7|4.3|1.9|3.4|\n|---|---|---|---|---|---|---|---|\n|ELEC|5|5|3|5|4|2|1|\n|GMSC|4|6|2|3|7|1|5|\n|POKR|4|4|6|3|7|1|2|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|1.3|2.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.1|5.8|4.2|2.9|4.7|1.8|3.2|\n\n### Delayed Kappa M\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|**100**|62.4|99.8|**100**|**100**|**100**|**100**|\n|LED G|**100**|59.7|**100**|**100**|**100**|**100**|99.6|\n|SEA A|**85.8**|73.9|82.3|85.6|59.2|85.4|76.4|\n|SEA G|**83.1**|68.9|80.6|82.7|45.7|82.7|71.4|\n|AGR A|16.0|12.6|-6.0|11.6|-12.6|**97.2**|61.8|\n|AGR G|14.5|14.3|10.8|14.7|18.5|**73.9**|61.2|\n|RTG  |17.6|22.7|31.1|31.2|22.6|**90.3**|22.2|\n|RBF F|-0.5|2.6|-2.4|-0.1|---|**4.1**|-8.0|\n|RBF M|13.8|-2.1|15.6|23.6|---|6.3|**24.7**|\n|HYPER|-1.7|-12.0|8.3|-103.0|-11.7|-0.7|**11.0**|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|42.9|30.3|42.0|34.6|40.2|**63.9**|52.0|\n|Synthetic Avg Rank|3.1|5.4|4.1|2.9|4.5|**1.9**|3.5|\n|---|---|---|---|---|---|---|---|\n|ELEC|-13.9|-13.9|0.0|-13.9|-13.3|1.2|**39.9**|\n|GMSC|-200.1|-224.7|0.0|-54.1|-1136.2|**2.9**|-200.8|\n|POKR|41.2|41.2|39.1|42.3|-4.1|**54.4**|44.4|\n|---|---|---|---|---|---|---|---|\n|Real Avg|-57.6|-65.8|13.0|-8.5|-384.5|**19.5**|-38.8|\n|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|**1.3**|2.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|19.7|8.1|35.3|24.7|-75.6|**53.7**|31.1|\n|Overall Avg Rank|3.4|5.3|4|3.1|4.9|**1.8**|3.3|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|1|7|6|1|1|1|1|\n|LED G|1|7|1|1|1|1|6|\n|SEA A|1|6|4|2|7|3|5|\n|SEA G|1|6|4|2|7|2|5|\n|AGR A|3|4|6|5|7|1|2|\n|AGR G|5|6|7|4|3|1|2|\n|RTG  |7|4|3|2|5|1|6|\n|RBF F|4|2|5|3|---|1|6|\n|RBF M|4|6|3|2|---|5|1|\n|HYPER|4|6|2|7|5|3|1|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|3.1|5.4|4.1|2.9|4.5|1.9|3.5|\n|---|---|---|---|---|---|---|---|\n|ELEC|5|5|3|5|4|2|1|\n|GMSC|4|6|2|3|7|1|5|\n|POKR|4|4|6|3|7|1|2|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|4.3|5.0|3.7|3.7|6.0|1.3|2.7|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|3.4|5.3|4|3.1|4.9|1.8|3.3|\n\n### Delayed CPU-Time\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|1012.091|795.131|893.665|820.796|288.025|**191.365**|373.476|\n|LED G|917.185|729.234|895.148|1000.183|309.330|**187.175**|398.284|\n|SEA A|269.649|346.151|250.556|255.098|209.188|**99.808**|152.553|\n|SEA G|300.443|347.493|283.960|255.368|197.863|**100.626**|151.474|\n|AGR A|383.949|364.802|859.119|405.709|292.374|**184.668**|349.424|\n|AGR G|388.325|384.454|407.795|404.792|339.822|**237.133**|323.537|\n|RTG  |316.509|273.405|292.777|294.298|233.565|**137.419**|220.481|\n|RBF F|860.316|886.757|795.317|869.959|---|**689.294**|826.780|\n|RBF M|858.122|833.409|785.766|894.627|---|**751.568**|814.607|\n|HYPER|287.258|254.839|239.510|254.784|202.320|**123.865**|233.962|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg|559.4|521.6|570.4|545.6|**259.1**|270.3|384.5|\n|Synthetic Avg Rank|5.8|5.0|4.7|5.5|2.5|**1.0**|2.6|\n|---|---|---|---|---|---|---|---|\n|ELEC|11.679|81.771|11.036|10.880|8.336|**4.550**|6.784|\n|GMSC|30.089|26.620|30.008|27.415|19.984|**7.512**|17.629|\n|POKR|746.798|652.104|694.198|688.450|**209.899**|458.636|618.694|\n|---|---|---|---|---|---|---|---|\n|Real Avg|262.9|253.5|245.1|242.2|**79.4**|156.9|214.4|\n|Real Avg Rank|6.7|5.0|5.7|4.7|2.3|**1.3**|2.3|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg|491.0|459.7|495.3|475.6|**210.1**|244.1|345.2|\n|Overall Avg Rank|6.0|5.0|4.9|5.3|2.5|**1.1**|2.5|\n\nRank Table:\n\n|Data set|ARSLVQ|RSLVQ SGD|RSLVQ ADA|RSLVQ RMS|Naive Bayes|Hoeffding Tree|Hoeffding Adaptive Tree|\n|---|---|---|---|---|---|---|---|\n|LED A|7|4|6|5|2|1|3|\n|LED G|6|4|5|7|2|1|3|\n|SEA A|6|7|4|5|3|1|2|\n|SEA G|6|7|5|4|3|1|2|\n|AGR A|5|4|7|6|2|1|3|\n|AGR G|5|4|7|6|3|1|2|\n|RTG  |7|4|5|6|3|1|2|\n|RBF F|4|6|2|5|---|1|3|\n|RBF M|5|4|2|6|---|1|3|\n|HYPER|7|6|4|5|2|1|3|\n|---|---|---|---|---|---|---|---|\n|Synthetic Avg Rank|   |   |   |   |   |   |   |\n|---|---|---|---|---|---|---|---|\n|ELEC|6|7|5|4|3|1|2|\n|GMSC|7|4|6|5|3|1|2|\n|POKR|7|4|6|5|1|2|3|\n|---|---|---|---|---|---|---|---|\n|Real Avg Rank|6.7|5.0|5.7|4.7|2.3|1.3|2.3|\n|---|---|---|---|---|---|---|---|\n|---|---|---|---|---|---|---|---|\n|Overall Avg Rank|6.0|5.0|4.9|5.3|2.5|1.1|2.5|\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffoxriver76%2Fmaster-thesis-rslvq","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffoxriver76%2Fmaster-thesis-rslvq","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffoxriver76%2Fmaster-thesis-rslvq/lists"}