public void New_Evaluation()
{
var dataPath = GetDataPath(SentimentDataPath);
var testDataPath = GetDataPath(SentimentTestPath);
using (var env = new LocalEnvironment(seed: 1, conc: 1))
{
var reader = new TextLoader(env, MakeSentimentTextLoaderArgs());
// Pipeline.
var pipeline = new TextLoader(env, MakeSentimentTextLoaderArgs())
.Append(new TextTransform(env, "SentimentText", "Features"))
.Append(new LinearClassificationTrainer(env, new LinearClassificationTrainer.Arguments {
NumThreads = 1
}, "Features", "Label"));
// Train.
var readerModel = pipeline.Fit(new MultiFileSource(dataPath));
// Evaluate on the test set.
var dataEval = readerModel.Read(new MultiFileSource(testDataPath));
var evaluator = new MyBinaryClassifierEvaluator(env, new BinaryClassifierEvaluator.Arguments()
{
});
var metrics = evaluator.Evaluate(dataEval);
}
}
