Exemplo n.º 1
0
func (*Tool) Run(args []string) {
	fmt.Println("running logistic regression")

	n := 1000
	p := 10

	beta := make([]float64, p)
	beta[0] = rand.NormFloat64()
	beta[1] = rand.NormFloat64()

	x := la.NewMatrix(n, p)
	y := la.NewVector(n)

	for i := 0; i < n; i++ {

		v := randVec(p)

		var z float64

		for j := 0; j < p; j++ {
			x.Set(i, j, v[j])
			z += beta[j]
		}

		if z > 0 {
			y.Set(i, +1)
		} else {
			y.Set(i, -1)
		}
	}

	rp := &model.RegressionProblem{
		N:            n,
		P:            p,
		Data:         x,
		Response:     y,
		ColumnNames:  names("p", p),
		RowNames:     names("x", n),
		ResponseName: "y",
	}

	rc := &model.LogisticRegressionRisk{}
	pc := model.NewLassoPenalty(p)

	dv := 0.001
	vmax := 0.07

	mon := &FixedVMonitor{vmax}

	oa := &model.RandomAssigner{rp.Data.Rows, 2.0 / 3.0}

	tt := oa.Assign()

	results := model.RunGpsFull(rp, tt, dv, rc, pc, mon.Continue)

	fmt.Println(results)

}
Exemplo n.º 2
0
func Load() (*model.RegressionProblem, *model.ObservationAssignments) {
	scanner := bufio.NewScanner(strings.NewReader(CancerDataCSV))
	var lines [][]string
	for scanner.Scan() {
		lines = append(lines, strings.Split(scanner.Text(), "\t"))
	}
	if scanner.Err() != nil {
		panic("can't read data")
	}

	var test, train []int

	var rowNames []string

	header := lines[0]
	m := la.NewMatrix(len(lines)-1, 8)
	for i := 0; i < m.Rows; i++ {
		for j := 0; j < m.Cols; j++ {
			if f, err := strconv.ParseFloat(strings.TrimSpace(lines[i+1][j+1]), 64); err == nil {
				m.Set(i, j, f)
			}
		}

		switch lines[i+1][10] {
		case "T":
			train = append(train, i)
		case "F":
			test = append(test, i)
		}

		rowNames = append(rowNames, lines[i+1][0])
	}

	y := la.NewVector(len(lines) - 1)
	for i := 0; i < y.Size; i++ {
		if f, err := strconv.ParseFloat(strings.TrimSpace(lines[i+1][9]), 64); err == nil {
			y.Set(i, f)
		}
	}

	out := model.RegressionProblem{
		N:            m.Rows,
		P:            m.Cols,
		Data:         m,
		Response:     y,
		ColumnNames:  header[1 : len(header)-2],
		RowNames:     rowNames,
		ResponseName: header[9],
	}

	tt := model.ObservationAssignments{
		TrainingIndicies: train,
		TestingIndicies:  test,
	}

	return &out, &tt
}