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我有一個用LinearRegression處理的DataFrame。如果我做它直接,像下面,我可以顯示模型的細節:如何訪問ML管道中基礎模型的參數?
val lr = new LinearRegression()
val lrModel = lr.fit(df)
lrModel: org.apache.spark.ml.regression.LinearRegressionModel = linReg_b22a7bb88404
println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
Coefficients: [0.9705748115939526] Intercept: 0.31041486689532866
然而,如果I(在下面的簡化示例等)使用它管線內部,
val pipeline = new Pipeline().setStages(Array(lr))
val lrModel = pipeline.fit(df)
那麼我得到以下錯誤。
scala> lrModel
res9: org.apache.spark.ml.PipelineModel = pipeline_99ca9cba48f8
scala> println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
<console>:68: error: value coefficients is not a member of org.apache.spark.ml.PipelineModel
println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
^
<console>:68: error: value intercept is not a member of org.apache.spark.ml.PipelineModel
println(s"Coefficients: ${lrModel.coefficients} Intercept: ${lrModel.intercept}")
我明白這意味着什麼(很明顯我有一個不同的類,因爲管道的),但不知道怎麼去真正的底層模型。