| // Licensed to the Apache Software Foundation (ASF) under one or more |
| // contributor license agreements. See the NOTICE file distributed with |
| // this work for additional information regarding copyright ownership. |
| // The ASF licenses this file to You under the Apache License, Version 2.0 |
| // (the "License"); you may not use this file except in compliance with |
| // the License. You may obtain a copy of the License at |
| // |
| // http://www.apache.org/licenses/LICENSE-2.0 |
| // |
| // Unless required by applicable law or agreed to in writing, software |
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| = Introduction |
| |
| Apache Ignite since 2.8 supports importing Machine Learning models from external platforms including Apache Spark ML and XGBoost. By working with imported models, you can: |
| |
| - store imported models in Ignite for further inference, |
| - use imported models as part of pipelines, |
| - apply ensembling methods such as boosting, bagging, or stacking to those models. |
| |
| Also, imported pre-trained models can be updated inside Apache Ignite. |
| |
| Apache Ignite provides an API for distributed inference for models trained in [Apache Spark ML], [XGBoost], and [H2O]. |
| |