Comments (3)
SkLearn2PMML versions 0.108.0 and newer support all InterpretML glassbox estimators, including the ExplainableBoostingClassifier
and ExplainableBoostingRegressor
estimator classes.
Here's a demo:
from interpret.glassbox import ExplainableBoostingClassifier
from sklearn2pmml import sklearn2pmml
classifier = ExplainableBoostingClassifier(random_state = 13)
classifier.fit(X, y)
sklearn2pmml(classifier, "EBM.pmml")
So, I believe this issue can be closed as "fixed" now.
from interpret.
Hi @lukedex -- I'm not aware of a PMML exporter for EBMs and a search on github for "explainable boosting" PMML yields no results, so if there is one it's very well hidden.
Given the development needs in other areas I probably won't work on this myself in the near term, but I'll leave it in our backlog, and would welcome a PR if anyone would like to contribute such an exporter.
from interpret.
Thank you @vruusmann, thatβs great news!
Closing the issue.
from interpret.
Related Issues (20)
- Integrate EBM into the pytorch framework HOT 7
- Visualising Decision Tree explainer gives a Cytoscape object which is not savable to my local machine HOT 2
- [DP-EBM] Question regarding range R and sensitivity
- Support for more parameters in the Differentially Private models HOT 1
- NAM Model HOT 1
- Some hyperparameter questions HOT 3
- Lookup Table for single feature and feature interaction terms HOT 5
- Operations when merging EBM HOT 6
- EBM Classifier Global Feature Importance x Random Forest Classifier with Morris Sensitivity Analysis HOT 1
- possibility of adding `sample_weight` to `interpret.glassbox.ClassificationTree` HOT 6
- 2d PDP Z-axis colours appear too similar HOT 1
- Feature Request: Passing Validation Set or Index HOT 2
- Explore the data with continuous output and category input HOT 4
- Using the init_score in EBM Classifier HOT 1
- Merging two EBM regressors leads to model that has NaNs in attributes HOT 1
- Bug: Pandas DataFrames columns names not verified at prediction time HOT 6
- Add a new interpretable algorithm, Automatic Piecewise Linear Regression HOT 11
- Smoothness over variable regions with outlier outcome values HOT 7
- Create submodels of an ExplainableBoostingRegressor(outer_bags=14)? HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
π 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. πππ
-
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 β€οΈ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from interpret.