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]]);
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.
