# MLJ NuSVM predict function not found
**URL:** https://discourse.julialang.org/t/mlj-nusvm-predict-function-not-found/105148
**Category:** General Usage
**Created:** [October 19, 2023, 1:57am UTC](https://discourse.julialang.org/t/mlj-nusvm-predict-function-not-found/105148 "2023-10-19T01:57:50Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@bryaan](https://discourse.julialang.org/u/bryaan)
#### Post date: [October 19, 2023, 1:57am UTC](https://discourse.julialang.org/t/mlj-nusvm-predict-function-not-found/105148/1 "2023-10-19T01:57:51Z")
I’m having an issue using MLJ NuSVR model. From the docs this should be working.
> **[NuSVR · MLJ](https://alan-turing-institute.github.io/MLJ.jl/dev/models/NuSVR_LIBSVM/)**
>
> Documentation for MLJ.
```julia
NuSVR = @load NuSVR pkg=LIBSVM
model = NuSVR(kernel=LIBSVM.Kernel.RadialBasis)
# SVMRegressor = @load SVMRegressor pkg=MLJScikitLearnInterface
# model = SVMRegressor()
mach = machine(model, X, y)
mach |> fit!
yhat = LIBSVM.predict(mach, Xnew)
```
I get this error:
```julia
MethodError: no method matching predict(::Machine{MLJLIBSVMInterface.NuSVR, true}, ::Vector{Float64})
Closest candidates are:
predict(::LIBSVM.LinearSVC, ::AbstractArray)
@ LIBSVM ~/.julia/packages/LIBSVM/IZl0L/src/ScikitLearnAPI.jl:11
predict(::Union{LIBSVM.AbstractSVC, LIBSVM.AbstractSVR}, ::AbstractArray)
@ LIBSVM ~/.julia/packages/LIBSVM/IZl0L/src/ScikitLearnAPI.jl:6
```
---
### Author:  [@math4mad](https://discourse.julialang.org/u/math4mad)
#### Post date: [October 19, 2023, 7:42am UTC](https://discourse.julialang.org/t/mlj-nusvm-predict-function-not-found/105148/2 "2023-10-19T07:42:53Z")
Checking `Xnew`’s type , should be same with `X`’s type
---
### Author:  [@math4mad](https://discourse.julialang.org/u/math4mad)
#### Post date: [October 19, 2023, 7:48am UTC](https://discourse.julialang.org/t/mlj-nusvm-predict-function-not-found/105148/3 "2023-10-19T07:48:13Z")
```julia
import LIBSVM
import MLJ:predict
using MLJ
NuSVR = @load NuSVR pkg=LIBSVM ## model type
model = NuSVR(kernel=LIBSVM.Kernel.Polynomial) ## instance
X, y = make_regression(rng=123) ## table, vector
mach = machine(model, X, y) |> fit!
Xnew, _ = make_regression(3, rng=123)
yhat = predict(mach, Xnew)
```
`import MLJ:predict` . so works!
---
### Author:  [@bryaan](https://discourse.julialang.org/u/bryaan)
#### Post date: [October 21, 2023, 3:01am UTC](https://discourse.julialang.org/t/mlj-nusvm-predict-function-not-found/105148/4 "2023-10-21T03:01:02Z")
Thank you!