PMML
- Anomaly Detection
- Association Rules
- Cluster
- General Regression
- k-Nearest Neighbors
- Naive Bayes
- Neural Network
- Regression
- Ruleset
- Scorecard
- Random Forest
- Decision Tree
- Vector Machine
- Multiple Models
Some Machine Learning tools and platforms can generate PMML models directly. Other models must be converted to PMML. For examples of Python pipelines that generate PMML models, see Python Pipelines for PMML Models.
MOJO
Vantage BYOM H2OPredict supports Driverless AI and H2O-3 MOJO models.
For examples of Python pipelines that generate MOJO models, see Python Code to Generate H2O Open Source Models.
ONNX
Vantage BYOM ONNXPredict supports models in ONNX format. Several training frameworks support native export functionality to ONNX, such as Chainer, Caffee2, and PyTorch. You can also convert models from several toolkits (such as, scikit-learn, TensorFlow, Keras, XGBoost, H2O, and Spark ML) to ONNX.
Dataiku
- Random Forest
- Gradient Tree Boosting
- Ordinary Least Squares
- Ride Regression
- Lasso Regression
- LightGBM
- XGBoost
- Decision Tree
- Support Vector Machine
- Stochastic Gradient Descent
- KNN
- Extra Random Trees
- Neural Network
- Lasso Path
DataRobot
Vantage BYOM DataRobotPredict function supports models that are available to download as Scoring Code in the DataRobot AI platform.
The Vantage BYOM DataRobotPredict function does not support the DataRobot explanations feature.