Comments (4)
Adding domain validation of the arguments passed to the hyper-params constructors is something I've been shoveling forward a bit too long! Thanks for reporting, feel free to go for a PR, otherwise, I'll likely get it done with 1-2 days.
from evotrees.jl.
MWE (taken from the example in docs):
using EvoTrees
using Random
x_train = randn(100, 10)
y_train = randn(100)
config = EvoTreeRegressor(
loss=:linear,
nrounds=100,
max_depth=6,
nbins=256,
eta=0.1,
lambda=0.1,
gamma=0.1,
min_weight=1.0,
rowsample=0.5,
colsample=0.8)
m = fit_evotree(config; x_train, y_train)
preds = m(x_train)
# throws: nested task error: InexactError: trunc(UInt8, 256)
Tested on the latest version in main.
versioninfo()
Julia Version 1.8.5
Commit 17cfb8e65ea (2023-01-08 06:45 UTC)
Platform Info:
OS: macOS (arm64-apple-darwin21.5.0)
CPU: 8 × Apple M1 Pro
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-13.0.1 (ORCJIT, apple-m1)
Threads: 6 on 6 virtual cores
from evotrees.jl.
I have too many other things going on this weekend, but I should be able to get to it on Monday.
When I find time, I'll check here if you've started or not.
from evotrees.jl.
I've hacked up a draft. Let me know what you think!
from evotrees.jl.
Related Issues (20)
- Using EvoTrees.jl for multi-target regression problems HOT 3
- Does not handle NaN HOT 4
- v1 roadmap
- Make CUDA a weak dependency HOT 3
- Probabilistic Forecast HOT 2
- Trains as single threaded and no documentation on how to use multithreading HOT 1
- Feature Request: piecewise linear gradient boosting tree HOT 2
- EvoTreeMLE retrun NaN HOT 2
- Initialization of rng HOT 2
- Shuffling feature order when changing seed HOT 5
- Document how missing values should be handled by user HOT 7
- Threading issue HOT 3
- Can't find plot function HOT 2
- Example for how to use EvoTrees.jl as a component of a more complicated model HOT 3
- Feature/Tutorial Request: Hyperparameter tuning HOT 5
- Categorical Variables Not Working HOT 7
- Citation HOT 6
- In MLJ interface, classifier makes unordered class predictions for ordered training target HOT 3
- Feature Request MultiQuantile HOT 1
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from evotrees.jl.