mirror of
https://github.com/sjwhitworth/golearn.git
synced 2025-04-26 13:49:14 +08:00
83 lines
2.2 KiB
Go
83 lines
2.2 KiB
Go
package linear_models
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import (
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"fmt"
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"github.com/sjwhitworth/golearn/base"
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)
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func generateClassWeightVectorFromDist(X base.FixedDataGrid) []float64 {
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classDist := base.GetClassDistributionByBinaryFloatValue(X)
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ret := make([]float64, len(classDist))
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for i, c := range classDist {
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if c == 0 {
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ret[i] = 1.0
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} else {
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ret[i] = 1.0 / float64(c)
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}
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}
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return ret
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}
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func generateClassWeightVectorFromFixed(X base.FixedDataGrid) []float64 {
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classAttrs := X.AllClassAttributes()
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if len(classAttrs) != 1 {
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panic("Wrong number of class Attributes")
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}
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if _, ok := classAttrs[0].(*base.FloatAttribute); ok {
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ret := make([]float64, 2)
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for i := range ret {
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ret[i] = 1.0
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}
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return ret
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} else {
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panic("Must be a FloatAttribute")
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}
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}
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func convertInstancesToProblemVec(X base.FixedDataGrid) [][]float64 {
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// Allocate problem array
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_, rows := X.Size()
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problemVec := make([][]float64, rows)
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// Retrieve numeric non-class Attributes
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numericAttrs := base.NonClassFloatAttributes(X)
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numericAttrSpecs := base.ResolveAttributes(X, numericAttrs)
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// Convert each row
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X.MapOverRows(numericAttrSpecs, func(row [][]byte, rowNo int) (bool, error) {
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// Allocate a new row
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probRow := make([]float64, len(numericAttrSpecs))
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// Read out the row
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for i, _ := range numericAttrSpecs {
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probRow[i] = base.UnpackBytesToFloat(row[i])
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}
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// Add the row
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problemVec[rowNo] = probRow
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return true, nil
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})
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return problemVec
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}
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func convertInstancesToLabelVec(X base.FixedDataGrid) []float64 {
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// Get the class Attributes
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classAttrs := X.AllClassAttributes()
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// Only support 1 class Attribute
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if len(classAttrs) != 1 {
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panic(fmt.Sprintf("%d ClassAttributes (1 expected)", len(classAttrs)))
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}
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// ClassAttribute must be numeric
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if _, ok := classAttrs[0].(*base.FloatAttribute); !ok {
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panic(fmt.Sprintf("%s: ClassAttribute must be a FloatAttribute", classAttrs[0]))
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}
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// Allocate return structure
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_, rows := X.Size()
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labelVec := make([]float64, rows)
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// Resolve class Attribute specification
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classAttrSpecs := base.ResolveAttributes(X, classAttrs)
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X.MapOverRows(classAttrSpecs, func(row [][]byte, rowNo int) (bool, error) {
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labelVec[rowNo] = base.UnpackBytesToFloat(row[0])
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return true, nil
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})
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return labelVec
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}
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