40:null 41:["$","title",null,{"children":"Logistic regression | Michael Metzler's Workspace | Observable"}] 47:[] 45:{"id":"1e3d6967c7422101","slug":null,"title":"Logistic regression","thumbnail":"51dc6b12513b4d9ad8da2dd7c341c14debe525b39e0166a6095eac0c8a883f9e","access_level":"public","create_time":"$D2023-10-03T12:08:06.037Z","update_time":"$D2023-10-03T12:54:19.924Z","view_time":null,"first_public_time":"$D2023-10-03T12:08:06.037Z","has_unpublished_edits":null,"fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"d729795dcee0f085","login":"michael-metzler-ws","name":"Michael Metzler's Workspace","avatar_url":"https://avatars-next.observableusercontent.com/64b3b0fb6d254ff7f9cff0abc3723cc9e37c91b026d0626a6a13f4fb921ce112","tier":"starter_2024","bio":"","following":false},"version":169,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"4d27dac4a6f09eae","login":"mmmmet14423","name":"Mike m","avatar_url":"https://avatars-next.observableusercontent.com/f70ad2e255cf5279c3607bc6b800e4e8ec314f4434ad8e65518bc342569e0816","tier":null,"bio":"","following":false}],"members":[{"type":"team","id":"d729795dcee0f085","login":"michael-metzler-ws","name":"Michael Metzler's Workspace","avatar_url":"https://avatars-next.observableusercontent.com/64b3b0fb6d254ff7f9cff0abc3723cc9e37c91b026d0626a6a13f4fb921ce112","tier":"starter_2024","role":"editor"},{"type":"individual","id":"4d27dac4a6f09eae","login":"mmmmet14423","name":"Mike m","avatar_url":"https://avatars-next.observableusercontent.com/f70ad2e255cf5279c3607bc6b800e4e8ec314f4434ad8e65518bc342569e0816","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":null,"type":"notebook","body":{"titling":"auto","title":"Logistic regression","cells":[{"id":0,"value":"# Logistic regression","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":135,"value":"viewof threshold = Inputs.range([0, 10], { step: 0.1 })","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":158,"value":"html`\n\n \n \n \n\n \n \n \n\n \n \n \n

	Predicted Negitive	Predicted Positive
Actual Positive	${falseNegitives}	${truePositive}
Actual Negitive	${trueNegitives}	${falsePositive}

\n`","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"Plot.plot({\n x: { domain: [0, 10] },\n y: { domain: [0, 1] },\n marks: [\n Plot.ruleX([0]),\n Plot.ruleY([0]),\n Plot.dot(Xblue, { x: Xblue, y: 0, fill: \"blue\" }),\n Plot.dot(Xred, { x: Xred, y: 0, fill: \"red\" }),\n Plot.line(\n [\n [threshold, 0],\n [threshold, 1]\n ],\n { strokeDasharray: \"5,5\" }\n )\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":139,"value":"trueNegitives = Xblue.filter((x) => x <= threshold).length","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":143,"value":"falseNegitives = Xred.filter((x) => x < threshold).length","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":149,"value":"truePositive = Xred.filter((x) => x > threshold).length","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"falsePositive = Xblue.filter((x) => x >= threshold).length","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":125,"value":"Xblue = [\n 3.319808626887721, 0.17267431749119444, 3.9232929828623093, 2.380555271252465,\n 1.349330931595207, 2.0066284426389007, 0.37158767653225766, 1.735205071058377,\n 2.0840286241446457, 1.187656369916016\n]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":127,"value":"Xred = [8.193605270661076, 8.729956729311493, 9.31683482651583, 7.704378276131655, 7.0565062978451, 6.0988732328264925, 6.341763176314117, 7.178519833406082, 7.113651611640721, 6.75916520727529]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":128,"value":"Yblue = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":131,"value":"Yred = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1]","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W47","stdlib":"1"}} 46:"$45:body"