pmml

Is there a way to export a gbm model to C++. Specifically, how do I invoke the predict.gbm function to run outside of R in order to score new datasets. I have exported the model as a PMML file but I am unsure as to how new datasets will be scores based off the PMML. I am new to R and have spent a lot of hours trying to figure this out to no avail and will appreciate any leads Thanks in advance Here, PMML only helps you if you have a C++ based PMML evaluation engine available (alternatively, you might use C++ to invoke a Java based PMML evaluation engine such as the JPMML-Evaluator library).

So this is a slightly insane idea that I've been kicking around. I'm thinking of building a classifier for (a specialized subset of) some web content, and then supplying it to users in the form of a chrome extension. (So: user goes to web page, clicks button on chrome extension, extension applies pre-trained model to generate prediction, presents result to user.) But I'm cheap, and I don't want to run a server to receive data from the chrome extension, generate a prediction, and send it back to the user. It occurs to me: why not just find some way to serialize the trained model or something,

I know that it's possible to export models as PMML with Spark-MLlib , but what about Spark-ML ? Is it possible to convert LinearRegressionModel from org.apache.spark.ml.regression to a LinearRegressionModel from org.apache.spark.mllib.regression to be able to invoke the toPMML() method? You can convert Spark ML pipelines to PMML using the JPMML-SparkML library: StructType schema = dataFrame.schema() PipelineModel pipelineModel = pipeline.fit(dataFrame); org.dmg.pmml.PMML pmml = org.jpmml.sparkml.ConverterUtil.toPMML(schema, pipelineModel); JAXBUtil.marshalPMML(pmml, new StreamResult(System.out

I have a PMML file of a trained Artificial Neural Network (ANN). I would like to create a Java method which simply takes in the inputs and returns the targeted value. This seems pretty easy, but I do not know how realize it. The PMML Version = 3.0 Update: 24.05.2013 I tried to use the jpmml Java API. This is how I have done: (1) Downloaded via Maven Central Repository ( link ) three .Jar files: pmml-manager-1.0.2.jar pmml-model-1.0.2.jar pmml-evaluator-1.0.2.jar (2) Used eclipse to "configure Build path" and added those three external .Jar's (3) Import my PMML-File named "text.xml" ( an

I am new to python,PMML and augustus,so this question kind of newbie.I have a PMML file from which i want to score after every new iteration of data. I have to use Python with Augustus only to complete this excercise. I have read various articles some of them worth mentioning as they are good. ( http://augustusdocs.appspot.com/docs/v06/model_abstraction/augustus_and_pmml.html , http://augustus.googlecode.com/svn-history/r191/trunk/augustus/modellib/regression/producer/Producer.py ) I have read augustus documentation relevent to scoring to understand how it works,but i am unable to solve this

I want to export python scikit-learn models into PMML. What python package is best suited? I read about Augustus , but I was not able to find any example using scikit-learn models. SkLearn2PMML is a thin wrapper around the JPMML-SkLearn command-line application. For a list of supported Scikit-Learn Estimator and Transformer types, please refer to the documentation of the JPMML-SkLearn project. As @user1808924 notes, it supports Python 2.7 or 3.4+. It also requires Java 1.7+ Installed via: (requires git ) pip install git+https://github.com/jpmml/sklearn2pmml.git Example of how export a