The avatar for @justingosses
Justin Gosses
JavaScript | Python | Data Visualization | Web Development | Geology | Space | Analytics | IoT | Learn, Build Stuff, and Figure Things Out
Published
Edited
Mar 25, 2018
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forest = require('https://bundle.run/random-forest-classifier@0.6.0')
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RandomForestClassifier = forest.RandomForestClassifier
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iris.length
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trainDataLength = iris.length*0.80
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irisTrain = iris.slice(0,trainDataLength)
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irisTest = iris.slice(trainDataLength,iris.length)
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rf = new RandomForestClassifier({
n_estimators: 10
})
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answer = []
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fit(irisTrain,["sepalLength", "sepalWidth"], "species", function(err,trees){getOut(rf.trees)})
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answerReally = pred(irisTest, answer)
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answerReally.length
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function getOut(pred){
answer.push(pred)
return answer
}
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rfNew = new RandomForestClassifier2({
n_estimators: 20
})
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fit2 = rfNew["fit"]
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pred2 = rfNew["predict"]
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answer2 = []
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// fit2(irisTrain, ["sepalLength", "sepalWidth"], "species",function(err,trees){getOut2(rfNew.trees)})
// fit(irisTrain,["sepalLength", "sepalWidth"], "species", function(err,trees){getOut(rf.trees)})
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// answerForPred2 = pred2(irisTest,answer2)
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fit2(irisTrain, ["sepalLength", "sepalWidth"], "species",function(err,trees){
let results2 = pred2(irisTest,trees)
console.log("test JUSTIN",trees)
// var pred = pred2(irisTest, rfNew.trees);
attemptArray.push(results2)
})
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