rf = import('https://cdn.skypack.dev/ml-random-forest@2.1.0?min')
regression = new rf.RandomForestRegression(options)
a = await regression.train(trainingSet, predictions);
result = a, regression.predict(trainingSet);
//result2 = a, regression.predict([[2,2200,7200,2,100,140,110]]);
result3 = a, regression.predict([[numericData[0],numericData[1],numericData[2],numericData[3],100,140,110]]);
//numericData[0]
viewof endofLife = Inputs.select(["Landfill","Downcycle","Recycle","Re-Manufacture","Reuse"], {label: "End of Life"})
viewof pctRecovered = Inputs.select(["0","50","100"], {label: "Percent Recovered",value:"50"})
viewof dist = Inputs.range([0, 1000], {step: 1, label: "Distance Traveled"})
viewof quant = Inputs.range([100, 1000], {step: 1, label: "Quantity"})
viewof set = Inputs.button("Set Data")
viewof dist.value
numericData = {
var data =[]
var eol
var rcvrd
var distance
var quantity
if(viewof endofLife.value=="Landfill"){eol = 1}
if(viewof endofLife.value=="Downcycle"){eol = 2}
if(viewof endofLife.value=="Recycle"){eol = 3}
if(viewof endofLife.value=="Re-Manufacture"){eol = 4}
if(viewof endofLife.value=="Reuse"){eol = 5}
if(viewof pctRecovered.value=="0"){rcvrd = 1}
if(viewof pctRecovered.value=="50"){rcvrd = 2}
if(viewof pctRecovered.value=="100"){rcvrd = 3}
distance = viewof dist.value
quantity = viewof quant.value
data.push(eol)
data.push(rcvrd)
data.push(distance)
data.push(quantity)
data.push(set)
return data
}
a, regression.featureImportance()
a, regression.toJSON()
SP - Materials for Machine Learning - Sheet3 (2).csv
Type Table, then Shift-Enter. Ctrl-space for more options.
spMaterialsForMachineLearningSheet3
fullDataSet = {
return spMaterialsForMachineLearningSheet3
}
formattedData = {
var fullSet = []
for (let i = 0; i < fullDataSet.length; i++) {
var currentLine = [Number(fullDataSet[i].col1),Number(fullDataSet[i].col2),Number(fullDataSet[i].col3),Number(fullDataSet[i].col4),Number(fullDataSet[i].col5),Number(fullDataSet[i].col6),Number(fullDataSet[i].col7),Number(fullDataSet[i].result)]
fullSet.push(currentLine)
}
return fullSet
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
