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33 lines
854 B
Go
33 lines
854 B
Go
package main
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import (
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"fmt"
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base "github.com/sjwhitworth/golearn/base"
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knnclass "github.com/sjwhitworth/golearn/knn"
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util "github.com/sjwhitworth/golearn/utilities"
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mat "github.com/skelterjohn/go.matrix"
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)
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func main() {
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//Parses the infamous Iris data.
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cols, rows, _, labels, data := base.ParseCsv("datasets/randomdata.csv", 2, []int{0, 1})
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newlabels := util.ConvertLabelsToFloat(labels)
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//Initialises a new KNN classifier
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knn := knnclass.KNNRegressor{}
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knn.New("Testing", newlabels, data, rows, cols)
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for {
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//Creates a random array of N float64s between 0 and Y
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randArray := util.RandomArray(2, 100)
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//Initialises a vector with this array
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random := mat.MakeDenseMatrix(randArray, 1, 2)
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//Calculates the Euclidean distance and returns the most popular label
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outcome, _ := knn.Predict(random, 3)
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fmt.Println(outcome)
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}
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}
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