CODIGO - Rocio-Mejia/Github-Flow GitHub Wiki

CÓDIGO

import org.apache.spark.ml.classification.{LogisticRegression, OneVsRest} import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator // $example off$ import org.apache.spark.sql.SparkSession

/**

• An example of Multiclass to Binary Reduction with One Vs Rest,
• using Logistic Regression as the base classifier.
• Run with
• {{{
• ./bin/run-example ml.OneVsRestExample
• }}} */

val spark = SparkSession.builder.appName(s"OneVsRestExample").getOrCreate()

// $example on$ // load data file. val inputData = spark.read.format("libsvm").load("spark/data/mllib/sample_multiclass_classification_data.txt") inputData.show() // generate the train/test split. val Array(train, test) = inputData.randomSplit(Array(0.8, 0.2))

// instantiate the base classifier val classifier = new LogisticRegression().setMaxIter(10).setTol(1E-6).setFitIntercept(true)

// instantiate the One Vs Rest Classifier. val ovr = new OneVsRest().setClassifier(classifier)

// train the multiclass model. val ovrModel = ovr.fit(train)

// score the model on test data. val predictions = ovrModel.transform(test)

// obtain evaluator. val evaluator = new MulticlassClassificationEvaluator().setMetricName("accuracy")

// compute the classification error on test data. val accuracy = evaluator.evaluate(predictions) println(s"Test Error = ${1 - accuracy}")