# Unable to find \`fit\` in \`CatBoost.MLJCatBoostInterface
**URL:** https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818
**Category:** Machine Learning
**Created:** [December 13, 2024, 5:37pm UTC](https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818 "2024-12-13T17:37:47Z")
**Posts on this page:** 5
**Page:** 1
### Author:  [@julien\_goo](https://discourse.julialang.org/u/julien_goo)
#### Post date: [December 13, 2024, 5:37pm UTC](https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818/1 "2024-12-13T17:37:47Z")
Hi!
I have developped a ML workflow using MLJ with some data preparation, feature engineer, cross-val and tuning (`evaluate!` function). Up to now, I used LightGBM (it worked fine), but since I have categorical variables, I wanted to test the performance with CatBoost.
I have an issue when using it. Despite having added Catboost and imported it, I keep having this message when the evaluation of the models starts.
```julia
Evaluating over 81 metamodels: 1%[>] ETA: 0:13:12┌ Error: Problem fitting the machine machine(DeterministicTunedModel(model = CatBoostRegressor(iterations = 1000, …), …), …).
└ @ MLJBase ~/.julia/packages/MLJBase/7nGJF/src/machines.jl:694
[ Info: Running type checks...
[ Info: Type checks okay.
ERROR: UndefVarError: `fit` not defined in `CatBoost.MLJCatBoostInterface`
Suggestion: check for spelling errors or missing imports.
Hint: a global variable of this name also exists in StatsBase.
Hint: a global variable of this name may be made accessible by importing Distributions in the current active module Main
Hint: a global variable of this name may be made accessible by importing GLM in the current active module Main
Hint: a global variable of this name may be made accessible by importing MLJModelInterface in the current active module Main
Hint: a global variable of this name may be made accessible by importing MLJBase in the current active module Main
Stacktrace:
[1] update(mlj_model::CatBoost.MLJCatBoostInterface.CatBoostRegressor, verbosity::Int64, fitresult::PythonCall.Core.Py, cache::@NamedTuple{…}, data_pool::PythonCall.Core.Py)
@ CatBoost.MLJCatBoostInterface ~/.julia/packages/CatBoost/8tf8r/src/MLJCatBoostInterface.jl:153
[2] fit_only!(mach::MLJBase.Machine{…}; rows::Vector{…}, verbosity::Int64, force::Bool, composite::Nothing)
@ MLJBase ~/.julia/packages/MLJBase/7nGJF/src/machines.jl:716
[3] fit_only!
@ ~/.julia/packages/MLJBase/7nGJF/src/machines.jl:617 [inlined]
...
```
Any recommendation to solve it?
Thx
---
### Author:  [@tylerjthomas9](https://discourse.julialang.org/u/tylerjthomas9)
#### Post date: [December 15, 2024, 4:43am UTC](https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818/2 "2024-12-15T04:43:32Z")
Thanks for reporting this! To better understand the issue, could you provide a Minimal Working Example (MWE) that reproduces the error?
---
### Author:  [@julien\_goo](https://discourse.julialang.org/u/julien_goo)
#### Post date: [December 15, 2024, 6:33am UTC](https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818/3 "2024-12-15T06:33:37Z")
Below is an MWE (extracted out of a heavy ML application). The package versions are reported at the end of the small script.
Thx for your help!
```using
using MLJ
using RDatasets
# Instantiate the model
CatBoostRegressor = @load CatBoostRegressor pkg=CatBoost
ml_model = CatBoostRegressor()
# Pipeline definition
pipe = ml_model
# Range
# LGBMRegressor
hp_ranges = [
range(pipe, :(iterations), lower = 30, upper = 300, scale=:log),
range(pipe, :(learning_rate), lower=0.01, upper=0.2, scale=:log),
range(pipe, :(depth), lower = 3, upper = 10, scale=:log),
range(pipe, :(subsample), lower = 0.6, upper = 1., scale=:linear),
range(pipe, :(l2_leaf_reg), lower = 3, upper = 100, scale=:log)
]
# My hyperparams grid
tuned_model = TunedModel(
model=pipe,
tuning=Grid(resolution=4),
ranges=hp_ranges,
measure=mae,
train_best=true,
cache=false,
compact_history=true,
)
# Prepare the data
y, x = unpack(
dataset("datasets", "iris"),
==(:SepalWidth)
)
# Define machine
mach = machine(
tuned_model,
x,
y,
cache=false,
scitype_check_level=2
)
# Evaluate
MLJ.evaluate!(
mach,
measure=mae,
acceleration=CPU1(),
verbosity=2,
per_observation=false
)
# With package versions:
# [cbdf2221] AlgebraOfGraphics v0.8.13
# [c6697862] AzStorage v2.7.0
# [6e4b80f9] BenchmarkTools v1.5.0
# [336ed68f] CSV v0.10.15
# ⌃ [13f3f980] CairoMakie v0.12.16
# [e2e10f9a] CatBoost v0.3.5
# [324d7699] CategoricalArrays v0.10.8
# [caabdcdb] Cleaner v1.1.1
# [944b1d66] CodecZlib v0.7.6
# [a93c6f00] DataFrames v1.7.0
# [864edb3b] DataStructures v0.18.20
# [89f0c457] FilesystemDatastructures v1.1.0
# ⌃ [cd3eb016] HTTP v1.10.12
# [f7bf1975] Impute v0.6.12
# [5903a43b] Infiltrator v1.8.3
# [c8e1da08] IterTools v1.10.0
# [9da8a3cd] JLSO v2.7.0
# [682c06a0] JSON v0.21.4
# [0f8b85d8] JSON3 v1.14.1
# [7acf609c] LightGBM v1.0.0
# [e6f89c97] LoggingExtras v1.1.0
# [add582a8] MLJ v0.20.7
# [a7f614a8] MLJBase v1.7.0
# [e80e1ace] MLJModelInterface v1.11.0
# [ce6b1742] RDatasets v0.7.7
# [295af30f] Revise v3.6.4
# [b0e4dd01] RollingFunctions v0.8.1
# [8523bd24] ShapML v0.3.2
# [1277b4bf] ShiftedArrays v2.0.0
# ⌃ [2913bbd2] StatsBase v0.34.3
# [69024149] StringEncodings v0.3.7
# [bd369af6] Tables v1.12.0
# [f269a46b] TimeZones v1.19.0
# [5c2747f8] URIs v1.5.1
# [ddb6d928] YAML v0.4.12
# [a5390f91] ZipFile v0.10.1
```
---
### Author:  [@tylerjthomas9](https://discourse.julialang.org/u/tylerjthomas9)
#### Post date: [December 15, 2024, 8:05pm UTC](https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818/4 "2024-12-15T20:05:22Z")
Thank you for reporting this. Can you verify that everything is working on your end? Here is the PR with the fix:
>
>
> It looks like the fix was just that we called \`fit\` instead of \`MMI.fit\` in the …\`MMI.update\` function.
---
### Author:  [@julien\_goo](https://discourse.julialang.org/u/julien_goo)
#### Post date: [December 15, 2024, 9:53pm UTC](https://discourse.julialang.org/t/unable-to-find-fit-in-catboost-mljcatboostinterface/123818/5 "2024-12-15T21:53:32Z")
> [@tylerjthomas9](#):
>
> [Fix #41, add tests around evaluate/tuning in MLJ by tylerjthomas9 · Pull Request #42 · JuliaAI/CatBoost.jl · GitHub](https://github.com/JuliaAI/CatBoost.jl/pull/42)
Hey,
It works perfect now. Thanks for the fix.