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Unable to convert scikit-leanr stack classifier with xgboost (1.5.2)

1

Hello, Using the latest onnxmltools I am getting a weird error: File "../python3.10/site-packages/onnxmltools/convert/xgboost/operator_converters/XGBoost.py", line 149, in _remap_nodeid nid = jsnode['nodeid'] I am using xgbosst 1.5.2. and i registered a xgboost...

azachar

KeyError: 'pyspark.ml.regression.IsotonicRegressionModel' when trying to convert Pyspark model to ONNX format

1

I am converting a pyspark trained model to ONNX format. More specifically, it's the pyspark.ml.regression.IsotonicRegressionModel. I get an error saying `KeyError: 'pyspark.ml.regression.IsotonicRegressionModel'. ` This is the piece of code I...

shyy5358

convert_xgboost - AssertionError: Missing required property "tree_info".

8

I was trying to run the sample code of convert_xgboost(onnxmltools/docs/examples/plot_convert_xgboost.py), and I got an error ["AssertionError: Missing required property "tree_info".] which is only for Dmatrix ( for sklearn model, it's...

ShuningL

sparkml utils.py getTensorTypeFromSpark for batch inputs; buildInputDictSimple excludes StringType()

1

1. getTensorTypeFromSpark() returns tensor types of shape [1,1]: This should be updated to [None,1] to accommodate batch data input. 2. buildInputDictSimple() only accounts for 'StringType' string dataType: This should also...

mattoh91

Hello, I'm trying to convert a pyspark.ml pipeline to onnx , but I get the following error. ``` from onnxmltools import convert_sparkml from skl2onnx.common.data_types import FloatTensorType onnx_model = convert_sparkml(model_multi, 'My...

thongvhoang

Hello, I'm trying to convert a pyspark.ml pipeline to onnx [StringIndexer, OneHotEncoder], but I get the following error. > RuntimeError: Operator pyspark_ml_feature_StringIndexerModel (type: pyspark.ml.feature.StringIndexerModel) got an input col_name with a...

mohaidoss

### Env - Python 3.9.7 - xgboost 1.5.2 - onnxmltools 1.11.0 ### Code to reproduce ```python import xgboost from onnxmltools.convert import convert_xgboost from onnxmltools.convert.common.data_types import FloatTensorType model = xgboost.XGBClassifier() model.load_model("xgb.ubj")...

hombit

KOLANICH

Spark XGB converter accesses missing param improperly

4

# Description https://github.com/onnx/onnxmltools/pull/373 introduced [this](https://github.com/onnx/onnxmltools/pull/373/files#diff-c697b8ded32498daeb86bb2eff12421758afc0de5079d749afe6520af20e885eR31-R33) constraint on the converter ```python if hasattr(xgb_node, 'missing') and not np.isnan(xgb_node.missing): raise RuntimeError("Cannot convert a XGBoost model where missing values are not " "nan but...

addisonklinke

Adding support for SHAP explainability to tree model types

1

[SHAP Explainability](https://shap.readthedocs.io/en/latest/example_notebooks/overviews/An%20introduction%20to%20explainable%20AI%20with%20Shapley%20values.html) provides an explanation for the output of a machine learning model. It provides insights as to how each feature contributes to the model's predictions, aiding in gaining an...

kikisq7