Comments (2)
To code more complicated loss that are not pointwise, you need implement https://github.com/tqchen/xgboost/blob/master/src/learner/objective.h#L13 IObjectiveFUnction, directly.
I guess AMS is not the metric you want to do gradient boosting on, it is unstable, and the true problem is overfitting instead of the correct objective.
Tianqi
from xgboost.
Thank you! Interesting answer, as always;)
from xgboost.
Related Issues (20)
- [R] CRAN warnings from clang18 HOT 5
- Does sample weights or scale_weight_pos affect leaf_value? HOT 3
- Build breaks on i386 HOT 2
- Predict_Proba method returns a float32 array, breaking scikit-learn compatibility HOT 3
- Categorical feature enumeration does not consider trivial split HOT 1
- xgbregressor and spark.SparkXGBRegressor giving very different results HOT 2
- 32-bit arch support and WASM HOT 4
- AttributeError: Can't get attribute '_can_use_qdm' on <module 'xgboost.sklearn' HOT 4
- Changing the order of rows in a toy dataset yields dramatically different predictions for XGBRanker HOT 3
- Global configuration could manage global number of threads HOT 4
- Integer overflow in `get_dump` and `trees_to_dataframe` HOT 1
- Model with External memory doesn't work with categorical features - with reproducible experiment (Python) HOT 1
- XGBoostError: [15:33:38] C:\buildkite-agent\builds\buildkite-windows-cpu-autoscaling-group-i-0b3782d1791676daf-1\xgboost\xgboost-ci-windows\src\data\data.cc:277: All feature_types must be one of {int, float, i, q, c}. HOT 1
- Ensure column order is correct in prediction validation. HOT 1
- Vertical Federated Learning with Secure Features (secure inference and encrypted training) RFC HOT 16
- Quantile regression example QuantileDMatrix construction HOT 1
- [dask] Example for forward logging.
- Features request - Conformal Prediction HOT 8
- Improve support for np type in parameters.
- Can I view individual XGBRFRegressor tree predictions? HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from xgboost.