{"action":"created","issue":{"url":"https://api.github.com/repos/berndbischl/mlrMBO/issues/100","labels_url":"https://api.github.com/repos/berndbischl/mlrMBO/issues/100/labels{/name}","comments_url":"https://api.github.com/repos/berndbischl/mlrMBO/issues/100/comments","events_url":"https://api.github.com/repos/berndbischl/mlrMBO/issues/100/events","html_url":"https://github.com/berndbischl/mlrMBO/issues/100","id":50165592,"number":100,"title":"gptk toolkit, learner for mlr","user":{"login":"berndbischl","id":1225974,"avatar_url":"https://avatars.githubusercontent.com/u/1225974?v=3","gravatar_id":"","url":"https://api.github.com/users/berndbischl","html_url":"https://github.com/berndbischl","followers_url":"https://api.github.com/users/berndbischl/followers","following_url":"https://api.github.com/users/berndbischl/following{/other_user}","gists_url":"https://api.github.com/users/berndbischl/gists{/gist_id}","starred_url":"https://api.github.com/users/berndbischl/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/berndbischl/subscriptions","organizations_url":"https://api.github.com/users/berndbischl/orgs","repos_url":"https://api.github.com/users/berndbischl/repos","events_url":"https://api.github.com/users/berndbischl/events{/privacy}","received_events_url":"https://api.github.com/users/berndbischl/received_events","type":"User","site_admin":false},"labels":[{"url":"https://api.github.com/repos/berndbischl/mlrMBO/labels/later","name":"later","color":"006b75"}],"state":"open","locked":false,"assignee":{"login":"jakobbossek","id":4079979,"avatar_url":"https://avatars.githubusercontent.com/u/4079979?v=3","gravatar_id":"","url":"https://api.github.com/users/jakobbossek","html_url":"https://github.com/jakobbossek","followers_url":"https://api.github.com/users/jakobbossek/followers","following_url":"https://api.github.com/users/jakobbossek/following{/other_user}","gists_url":"https://api.github.com/users/jakobbossek/gists{/gist_id}","starred_url":"https://api.github.com/users/jakobbossek/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jakobbossek/subscriptions","organizations_url":"https://api.github.com/users/jakobbossek/orgs","repos_url":"https://api.github.com/users/jakobbossek/repos","events_url":"https://api.github.com/users/jakobbossek/events{/privacy}","received_events_url":"https://api.github.com/users/jakobbossek/received_events","type":"User","site_admin":false},"milestone":null,"comments":3,"created_at":"2014-11-26T13:00:31Z","updated_at":"2015-02-06T16:59:30Z","closed_at":null,"body":"http://cran.r-project.org/web/packages/gptk/index.html\r\n\r\nIntegrate GP learners from the package as learners for mlr, so we can use them in mlrMBO.\r\n\r\nInsightful examples seem to be in inst/doc/index.html in the package.\r\n\r\n"},"comment":{"url":"https://api.github.com/repos/berndbischl/mlrMBO/issues/comments/73271254","html_url":"https://github.com/berndbischl/mlrMBO/issues/100#issuecomment-73271254","issue_url":"https://api.github.com/repos/berndbischl/mlrMBO/issues/100","id":73271254,"user":{"login":"berndbischl","id":1225974,"avatar_url":"https://avatars.githubusercontent.com/u/1225974?v=3","gravatar_id":"","url":"https://api.github.com/users/berndbischl","html_url":"https://github.com/berndbischl","followers_url":"https://api.github.com/users/berndbischl/followers","following_url":"https://api.github.com/users/berndbischl/following{/other_user}","gists_url":"https://api.github.com/users/berndbischl/gists{/gist_id}","starred_url":"https://api.github.com/users/berndbischl/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/berndbischl/subscriptions","organizations_url":"https://api.github.com/users/berndbischl/orgs","repos_url":"https://api.github.com/users/berndbischl/repos","events_url":"https://api.github.com/users/berndbischl/events{/privacy}","received_events_url":"https://api.github.com/users/berndbischl/received_events","type":"User","site_admin":false},"created_at":"2015-02-06T16:59:30Z","updated_at":"2015-02-06T16:59:30Z","body":"Example from SW which might help\r\n\r\n\r\n```\r\n\r\nlibrary(gptk)\r\n\r\nxValues = as.matrix(sample(seq(-0.0, 1.0, 0.001), 5))\r\nyValues = as.matrix(runif(5))\r\n\r\noptions = gpOptions()\r\n#options$learnScales = TRUE\r\n#options$optimiseBeta = TRUE\r\n#options$computeS = TRUE\r\noptions$kern$comp = list(\"rbf\")#, \"white\")\r\nmodel = gpCreate(1, 1, xValues, yValues, options)\r\nmodel = gpOptimise(model, 2, 10, TRUE)\r\n\r\nxTest = as.matrix(seq(-0.2, 1.2, 0.001))\r\noutData = gpPosteriorMeanVar(model, xTest, TRUE)\r\nyPred = outData$mu\r\nyVar = sqrt(pmax(0, outData$varsigma))\r\n\r\ngpPlot(model, xTest, yPred, yVar, col=\"black\")\r\n\r\n\r\n###################################################################\r\n\r\n\r\nlibrary(tgp)\r\n\r\nxValues = as.matrix(sample(seq(-0.0, 1.0, 0.001), 5))\r\nyValues = as.matrix(runif(5))\r\nxTest = as.matrix(seq(-0.2, 1.2, 0.001))\r\n\r\n#tgp.default.params(1)\r\nmodel = bgp(xValues, yValues, XX=xTest, corr=\"exp\", bprior=\"bmle\")\r\nplot(model)\r\n\r\n```\r\n"}}