Comments (2)
<RegressionModel functionName="classification" normalizationMethod="softmax">
<MiningSchema>
<MiningField name="label" usageType="target"/>
<MiningField name="message"/>
</MiningSchema>
<Output>
<OutputField name="pmml(prediction)" optype="categorical" dataType="string" isFinalResult="false"/>
<OutputField name="prediction" optype="continuous" dataType="double" feature="transformedValue">
<MapValues outputColumn="data:output" dataType="double">
<FieldColumnPair field="pmml(prediction)" column="data:input"/>
<InlineTable>
<row>
<data:input>A020901</data:input>
<data:output>0</data:output>
</row>
<row>
<data:input>A020304</data:input>
<data:output>1</data:output>
</row>
<row>
<data:input>A010903</data:input>
<data:output>2</data:output>
</row>
<row>
<data:input>A020204</data:input>
<data:output>3</data:output>
</row>
<row>
<data:input>A011603</data:input>
<data:output>4</data:output>
</row>
<row>
<data:input>A011504</data:input>
<data:output>5</data:output>
</row>
</InlineTable>
</MapValues>
</OutputField>
<OutputField name="probability(A020901)" optype="continuous" dataType="double" feature="probability" value="A020901"/>
<OutputField name="probability(A020304)" optype="continuous" dataType="double" feature="probability" value="A020304"/>
<OutputField name="probability(A010903)" optype="continuous" dataType="double" feature="probability" value="A010903"/>
<OutputField name="probability(A020204)" optype="continuous" dataType="double" feature="probability" value="A020204"/>
<OutputField name="probability(A011603)" optype="continuous" dataType="double" feature="probability" value="A011603"/>
<OutputField name="probability(A011504)" optype="continuous" dataType="double" feature="probability" value="A011504"/>
</Output>
from jpmml-evaluator-spark.
First, obtain the underlying org.jpmml.evaluator.Evaluator
instance via org.jpmml.evaluator.spark.PMMLTransformer#getEvaluator()
. Then invoke Evaluator#getMiningFunction()
.
from jpmml-evaluator-spark.
Related Issues (20)
- Invalid lambda deserialization at org.shaded.jpmml.evaluator.OutputFilters.$deserializeLambda$ HOT 4
- Rename transformer and transformer builder classes
- Simple prediction mode
- Model "data schema" exploration methods
- Replace `java.util.List<E>` parameters with `E[]` parameters in method signatures
- Row-oriented exception handling
- question about class 'PMMLTransformer' HOT 1
- question about build error HOT 1
- local class incompatible HOT 2
- dependency version not consistent HOT 2
- how to improve my pmml model‘s accuracy rate HOT 1
- submit spark job==》java.io.IOException: unexpected exception type HOT 1
- when i only use jpmml-evaluator-spark, it will incur an exception HOT 3
- reading pmml from hdfs HOT 1
- Resolving an application classpath conflict HOT 2
- Can I use Scala to load PMML model to complete prediction? HOT 1
- support for spark 3.x ? HOT 5
- The period (.) in <output> creates problems
- Incomplete `TransformerBuilder` default configuration for `exploded(true)`
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 jpmml-evaluator-spark.