Comments (4)
Commit identifiers got updated in early February 2017 when tagging all sklearn2pmml
release versions. So, let's talk in terms of release versions (see https://github.com/jpmml/sklearn2pmml/releases), not commit identifiers, from now on.
To produce PMML 4.2, you must use a sklearn2pmml
release version that includes JPMML-SkLearn version 1.0-SNAPSHOT
dependency. The last one to do so is version 0.9.7:
https://github.com/jpmml/sklearn2pmml/releases/tag/0.9.7
You should be able to get it like this:
pip install --user git+https://github.com/jpmml/[email protected]
from sklearn2pmml.
PMMLPipeline is not available.
Python class sklearn2pmml.PMMLPipeline
was introduced in sklearn2pmml
version 0.14.0.
If you're using a legacy version of sklearn2pmml
package (such as 0.9.7), then you must consult the corresponding README.md file for usage instructions.
from sklearn2pmml.
Thanks.
from sklearn2pmml.
which release for PMML 4.2 is the lastest?
from sklearn2pmml.
Related Issues (20)
- Patching 0.51.1 for unknown categorical variables HOT 4
- Postprocessing the probabilities of an XGBoost Model HOT 3
- Link Estimator with prefit=True doesn't work
- Support for the `OneHotEncoder.infrequent_categories_` attribute HOT 1
- Revert PMML file to Python source code HOT 1
- Error when using `TargetEncoder` within `DataFrameMapper` within pipeline HOT 6
- Missing dependency `dill` from `setup.py`. HOT 7
- Support for Python power operator `**` HOT 1
- Assembling a pipeline from pre-fitted components HOT 3
- looking for support on quantile_forest for RandomForestQuantileRegressor HOT 2
- Failing to convert `CalibratedClassifierCV` plus `XGBClassifier` combination HOT 12
- Effectively debugging XGBoost pipelines (mis-matching predictions between Python and (J)PMML) HOT 14
- Revisit the missing value handling of custom transformers HOT 1
- Support for AgglomerativeClustering HOT 2
- `ExpressionTransformer` should try to rectify feature type information HOT 5
- `Alias` object has no attribute `transformer_` HOT 8
- Storing LinearSVC as coefficients instead of support vectors HOT 1
- Reshape transformation results from 2-D to 1-D (column vectors) HOT 1
- sklearn2pmml does not work with sklearn version 1.3.0 and newer HOT 6
- sklearn2pmml does not work with xgboost >= 2.0.0 HOT 9
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 sklearn2pmml.