{"id":21374872,"url":"https://github.com/banool/comp30018-assn2","last_synced_at":"2026-01-03T01:40:00.999Z","repository":{"id":90881342,"uuid":"69723302","full_name":"banool/comp30018-assn2","owner":"banool","description":"Assignment 2 for COMP30018 - Knowledge Technologies. The report is the main part, python scikit code also included.","archived":false,"fork":false,"pushed_at":"2017-10-19T03:53:23.000Z","size":22045,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-14T23:43:22.575Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"HTML","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/banool.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":"2016-10-01T06:28:55.000Z","updated_at":"2017-10-10T00:17:02.000Z","dependencies_parsed_at":null,"dependency_job_id":"da58bcb3-b059-493b-ae27-3ee2a5551525","html_url":"https://github.com/banool/comp30018-assn2","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/banool%2Fcomp30018-assn2","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/banool%2Fcomp30018-assn2/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/banool%2Fcomp30018-assn2/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/banool%2Fcomp30018-assn2/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/banool","download_url":"https://codeload.github.com/banool/comp30018-assn2/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243848105,"owners_count":20357491,"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":"2024-11-22T08:45:57.831Z","updated_at":"2026-01-03T01:40:00.955Z","avatar_url":"https://github.com/banool.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Knowledge Technologies Assignment 2\n\n`ml.py` is the main script. The layout is a bit messy, but considering that it's\nnot marked quite a bit of work went into making it easily extensible for both\nadditional classifiers as well as additional evaluation methods. There is also\nfunctionality which pickles the processed data pulled from the arff files, which\ncuts down the time of each run enormously (from the order of 5 minutes for the\n446 training dataset down to a few seconds).\n\nJust try to run ml.py and it'll print usage information. Use it like this:\n\n`./ml.py 446 nb macro`\n\nThe averaging type (e.g. \"macro\") is optional.\n\nThe supported datasets are 35 and 446. These represent the development datasets.\nIf you want to use the test sets instead, the syntax is 35test and 446test.\nIf you run the scripts with the test sets, it will crash after generating the\npredictions (since there are no labels with which to evaluate), but everything\nup to that point, including the predictions, will work fine.\n\nThe classifiers are nb, svm and nbBoosted, from an earlier idea where I would\nexperiment with boosting the algorithm with AdaBoost and changing the kernel\nfor SVM.\n\n`plot_confusion_matrix.py` is just some script from the sci-kit documentation\nwhich I modified, all it does is print a graphical confusion matrix.\nSource here: https://goo.gl/XwMr6N\n\nPredictions have been included for the four primary datasets considered. If\nmarking requires only one set, use predictedNB446test, as it has the best\nresults. These are of course for the test data, not the dev data.\n\n## Results\n\nFinal result: 14.5/15\n\nCritical analysis: 6.5/7 || Technical Tasks: 1/1 || Creativity: 1/1 || Report quality: 3/3 || Reviews: 3/3\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbanool%2Fcomp30018-assn2","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbanool%2Fcomp30018-assn2","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbanool%2Fcomp30018-assn2/lists"}