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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
34 lines
824 B
Go
34 lines
824 B
Go
package base
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import "testing"
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func TestDecomp(testEnv *testing.T) {
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inst, err := ParseCSVToInstances("../examples/datasets/iris_binned.csv", true)
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if err != nil {
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testEnv.Error(err)
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return
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}
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decomp := inst.DecomposeOnAttributeValues(inst.GetAttr(0))
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row0 := decomp["0.00"].RowStr(0)
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row1 := decomp["1.00"].RowStr(0)
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/* row2 := decomp["2.00"].RowStr(0)
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row3 := decomp["3.00"].RowStr(0)
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row4 := decomp["4.00"].RowStr(0)
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row5 := decomp["5.00"].RowStr(0)
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row6 := decomp["6.00"].RowStr(0)
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row7 := decomp["7.00"].RowStr(0)*/
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row8 := decomp["8.00"].RowStr(0)
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// row9 := decomp["9.00"].RowStr(0)
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if row0 != "3.10 1.50 0.20 Iris-setosa" {
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testEnv.Error(row0)
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}
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if row1 != "3.00 1.40 0.20 Iris-setosa" {
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testEnv.Error(row1)
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}
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if row8 != "2.90 6.30 1.80 Iris-virginica" {
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testEnv.Error(row8)
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}
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}
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