Comments (3)
My internal TODO list has quite a few open items about the pandas.Int64Dtype
data type support.
The current issue can be corrected by initializing the CategoricalDomain.data_values_
attribute using the data_values
constructor parameter:
cat_domain = CategoricalDomain(data_values = [[1, 2, 3]])
Alternatively, a problematic attribute may be manually simplified to a dense/unmasked numpy array:
cat_domain.data_values_ = numpy.asarray(cat_domain.data_values_.tolist())
Perhaps such simplification should be applied automatically by the CategoricalDomain.fit(X, y)
method.
from sklearn2pmml.
Thanks for the quick response.
The suggested solution resolves the issue.
from sklearn2pmml.
Reopening, because the conversion should succeed without any manual intervention.
from sklearn2pmml.
Related Issues (20)
- 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
- LookupTransformer TypeError when default value is not exactly the type from the mapping HOT 2
- xgb 生成的pkl 转pmml 失败 HOT 1
- Can sklearn2pmml just for variable transformations be used? HOT 1
- PyPMML is making systematically off predictions with XGBoost PMML documents? HOT 16
- ImportError: cannot import name 'LabelBinarizer' from 'sklearn2pmml.preprocessing' HOT 2
- Compatibility with Scikit-Learn 1.4.0 HOT 8
- Convenience API for embedding model evaluation metrics as `ModelExplanation` element HOT 13
- Ability to "refine" (categorical-) valid value spaces along the transformer pipeline HOT 17
- NullPointerException when using OneHotEncoder with Integer Categorical Variables in sklearn2pmml HOT 10
- Create .pmml File for Calibrated xgboost Model HOT 8
- Pandas 2.2 FutureWarning for time series offset aliases HOT 2
- Pandas not installed as dependency 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 sklearn2pmml.