Изменения
→Линейная регрессия
plot(x, y, KNN)
===Линейная регрессия===
Sbt зависимость:
libraryDependencies += "org.apache.spark" %% "spark-mllib" % "2.4.0" % "runtime"
Пример линейной регрессии c применением org.apache.spark.ml.regression.LinearRegression<ref>[https://spark.apache.org/docs/latest/ml-classification-regression.html#linear-regression Spark ML, LinearRegression]</ref>:
val training = spark.read.format("libsvm")
.load("linear_regression.txt")
val lr = new LinearRegression()
.setMaxIter(10)
.setRegParam(0.3)
.setElasticNetParam(0.8)
val lrModel = lr.fit(training)
Вывод итоговых параметров модели:
println(lrModel.coefficients)
println(lrModel.intercept)
val trainingSummary = lrModel.summary
println(trainingSummary.totalIterations)
println(trainingSummary.objectiveHistory.mkString(","))
trainingSummary.residuals.show()
println(trainingSummary.rootMeanSquaredError)
println(trainingSummary.r2)
== Примечания ==
<references/>
