# Custom XGBoost Loss function w/ Zygote. Julia Computing blog post

**URL:** <https://discourse.julialang.org/t/custom-xgboost-loss-function-w-zygote-julia-computing-blog-post/35811>\
**Category:** Machine Learning\
**Tags:** zygote, kaggle\
**Created:** [March 10, 2020, 8:42pm UTC](https://discourse.julialang.org/t/custom-xgboost-loss-function-w-zygote-julia-computing-blog-post/35811 "2020-03-10T20:42:21Z")\
**Posts on this page:** 1\
**Showing post:** 35

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**Author:** ![nilshg](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nilshg/32/2283_2.png) [@nilshg](https://discourse.julialang.org/u/nilshg)\
**Post date:** [April 27, 2020, 7:51am UTC](https://discourse.julialang.org/t/custom-xgboost-loss-function-w-zygote-julia-computing-blog-post/35811/35 "2020-04-27T07:51:36Z")

</div>

Just construct a DataFrame from the names and scores?

```julia
julia> using DataFrames

julia> m_names = ["EvoTreeRegressor", "BaggingRegressor"];

julia> sc = [2.5212, 2.5358];

julia> DataFrame(Model = m_names, RMSE = sc)
2×2 DataFrame
│ Row │ Model │ RMSE │
│ │ String │ Float64 │
├─────┼──────────────────┼─────────┤
│ 1 │ EvoTreeRegressor │ 2.5212 │
│ 2 │ BaggingRegressor │ 2.5358 │

```

You can still display that in Juno with `showtable` but also write it to csv with `CSV.write("results.csv", df)`

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