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https://github.com/sjwhitworth/golearn.git
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a2c67592df
* Refactors KNNClassifier to use them * csv handling moved back into base due to a circular dependency * Also adds the datasets used to test CSV handling
33 lines
855 B
Go
33 lines
855 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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evaluation "github.com/sjwhitworth/golearn/evaluation"
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knn "github.com/sjwhitworth/golearn/knn"
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)
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func main() {
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rawData, err := base.ParseCSVToInstances("datasets/iris_headers.csv", true)
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if err != nil {
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panic(err)
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}
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rawData.Shuffle()
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//Initialises a new KNN classifier
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cls := knn.NewKnnClassifier("euclidean", 2)
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//Do a training-test split
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trainTest := base.InstancesTrainTestSplit(rawData, 0.50)
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trainData := trainTest[0]
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testData := trainTest[1]
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cls.Fit(trainData)
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//Calculates the Euclidean distance and returns the most popular label
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predictions := cls.Predict(testData)
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fmt.Println(predictions)
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// Prints precision/recall metrics
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confusionMat := evaluation.GetConfusionMatrix(testData, predictions)
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fmt.Println(evaluation.GetSummary(confusionMat))
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}
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