error while trying to fit the Gaussian Process Regressor

Hello! I am really new to this topic and golang in general, so sorry if this is too obvious

But i ran into the problem

I am trying to run the simple GP with the help of YouTube and ChatGPT, but my below code fails

package main

import (
    "fmt"
    "github.com/pa-m/sklearn/gaussian_process"
    "github.com/pa-m/sklearn/gaussian_process/kernels"
    "gonum.org/v1/gonum/mat"
    "log"
    "math/rand"
)

func main() {
    // Generate some sample data
    X := mat.NewDense(10, 1, nil)
    y := make([]float64, 10)
    for i := 0; i < 10; i++ {
        X.Set(i, 0, float64(i))
        y[i] = float64(i*i) + rand.NormFloat64() // Adding some noise
    }

    yMat := mat.NewDense(len(y), 1, y)

    // Print the training data for debugging
    fmt.Println("Training data X:")
    matPrint(X)
    fmt.Println("Training data y:")
    fmt.Println(yMat)

    // Define the kernel: ConstantKernel * RBF
    constantKernel := &kernels.ConstantKernel{ConstantValue: 1.0, ConstantValueBounds: [2]float64{1e-5, 1e5}}
    rbfKernel := &kernels.RBF{LengthScale: []float64{1.5}, LengthScaleBounds: [][2]float64{{1e-5, 1e5}}}
    productKernel := &kernels.Product{
        KernelOperator: kernels.KernelOperator{
            K1: constantKernel,
            K2: rbfKernel,
        },
    }
    // Create the Gaussian Process Regressor
    gp := gaussianprocess.NewRegressor(productKernel)

    // Print Alpha for debugging
    fmt.Println("Alpha:", gp.Alpha)

    // Fit the model with X and yVec
    err := gp.Fit(X, yMat)
    if err != nil {
        log.Fatalf("Error fitting model: %v", err)
    }

    // Print fitted model info
    fmt.Println("Model fitted successfully.")
    fmt.Println("Xtrain:", gp.Xtrain)
    fmt.Println("Ytrain:", gp.Ytrain)

    // Predict new values
    X_test := mat.NewDense(5, 1, []float64{0, 2, 4, 6, 8})
    y_pred := gp.Predict(X_test, nil)

    // Print the test data and prediction results for debugging
    fmt.Println("Test data X_test:")
    matPrint(X_test)
    fmt.Println("Predicted values:")
    matPrint(y_pred)
}

// Helper function to print matrix
func matPrint(X mat.Matrix) {
    fr, fc := X.Dims()
    for r := 0; r < fr; r++ {
        for c := 0; c < fc; c++ {
            fmt.Printf("%f ", X.At(r, c))
        }
        fmt.Println()
    }
}

the output i am getting is below

Training data X:
0.000000 
1.000000 
2.000000 
3.000000 
4.000000 
5.000000 
6.000000 
7.000000 
8.000000 
9.000000 
Training data y:
&{{10 1 [0.5188212784827827 1.6037047407115053 3.7898678224401436 9.925588854546554 14.542592015266568 24.547637573998195 35.40832007088673 47.42076179321582 64.03240815464373 82.19464262249846] 1} 10 1}
1
Alpha: [1e-10]
2024/07/11 18:52:45 Error fitting model: 1**2 * RBF([1.5])

I cannot understand what that error about fitting model means

I analyzed the fit method's code and cannot see where it can go wrong, or I am just blind

Would really appreciate the help! Thanks for the hard work

pa-m / sklearn

error while trying to fit the Gaussian Process Regressor #22