Scala MLlib Spark中MultilayerPerceptronClassifier函数的输入格式应该是什么？

我有这个示例代码。输入文件“data/mllib/sample\u multiclass\u classification\u data.txt”的格式如下：

import org.apache.spark.ml.classification.MultilayerPerceptronClassifier
import org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
import org.apache.spark.mllib.util.MLUtils
import org.apache.spark.sql.Row

// Load training data
val data = MLUtils.loadLibSVMFile(sc,"data/mllib/sample_multiclass_classification_data.txt").toDF()
// Split the data into train and test
val splits = data.randomSplit(Array(0.6, 0.4), seed = 1234L)
val train = splits(0)
val test = splits(1)
// specify layers for the neural network: 
// input layer of size 4 (features), two intermediate of size 5 and 4 and output of size 3 (classes)
val layers = Array[Int](4, 5, 4, 3)
// create the trainer and set its parameters
val trainer = new MultilayerPerceptronClassifier()
  .setLayers(layers)
  .setBlockSize(128)
  .setSeed(1234L)
  .setMaxIter(100)
// train the model
val model = trainer.fit(train)
// compute precision on the test set
val result = model.transform(test)
val predictionAndLabels = result.select("prediction", "label")
val evaluator = new MulticlassClassificationEvaluator().setMetricName("precision")
println("Precision:" + evaluator.evaluate(predictionAndLabels))

我的输入文件（CSV）：

我的输出如下所示：

关键余额-0.0036513722,7.4863195E-4,0.0026168288,0.0018019283,3.6993028E-5,0.0015877665，-0.0023806596，-0.0044850614,0.0030128842，-0.0027919186,0.0029404194,0.001331976，-0.002444722，-0.0022837287,0.0033935083，-1.0614514E-4,0.004019062,0.001854306,28591,0.001875，-0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.0.414178787-4、-4.0.978080808080807-4-4-4-4-4-4-4-4-4-4-4-4.0.0.0.97808080808080807 7 7-7-7-5-5-5-5-4-4-5-4-5-4.0.0.97808080808080807-5-5-5-5-5-5-4-5-4-5-4-5-4-5-5-4-5-5-4-5-4.5-5-5-5-5-4-5-5-4.0.5-5-5-5-5-5-4.0.0.978080808080808080285，-0.0045714066，-其中，0.00449494503-3.7978787-3-3-3.78787878787-3.7978787-3-3.797878787-7-3-3.7878787 7 7 7 7 7 7-4，-0.0.00235959877 7-4-0.7978787878787 7 7 7 7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7-7.78787878787878787-7-7-7-7-7-7，-0.78787878787878787878787-7-4，-0.78787-0.7878787-0.7878787-0.78787-0.787-0-0.7878787878787-0.787-0.787-0-7-0 8982，-0.0.0.2123734-4-0.0.41414848484848404040404040404040404040404040404041414141414141414141414141414141414141414141414141414141414141414141414141414141414-4-4-4-4.0.0.0.0.2123232373737314-0.0.0.0.0.0.0.0.0.0.0 0.2123232373737373737314、0.0.0.0.0.0.0 0 0 0 0 0.0.0 0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0 0.0 0 0 0.0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.0 0 0 0 0 0 0 0.0 0 0 0 0.0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 37607,6.298947E-4,0.00294445，-2.794385E-4，-0.004432401,0.0034545213,0.002706862

我想执行以下操作：输入->word2vec->输出->神经网络，

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但是示例代码的输出格式与我的输出不匹配。有人能帮我吗？

你能显示示例代码的输出吗？问题已解决。谢谢你，你应该在将来发布答案来帮助与你相同的人。word2vector的输出如下：[-0.069206687747853142,0.04828440344759396,0.0406973444185900874，-0.017867059313825196]MultilayerPerceptronClassifier的输入应采用以下格式：3 1:-0.040327 2:0.054813 3:0.034227 4:-0.033958，其中3表示标签或类别，1,2,3,4表示功能数量。是否显示示例代码的输出？问题已解决。谢谢你，你应该在将来发布答案来帮助与你相同的人。word2vector的输出如下：[-0.069206687747853142,0.04828440344759396,0.0406973444185900874，-0.017867059313825196]多层受体分类器的输入应采用以下格式：3 1:-0.040327 2:0.054813 3:0.034227 4:-0.033958，其中3表示标签或类别，1,2,3,4表示特征数量

1 1:-0.222222 2:0.5 3:-0.762712 4:-0.833333 
1 1:-0.555556 2:0.25 3:-0.864407 4:-0.916667 
1 1:-0.722222 2:-0.166667 3:-0.864407 4:-0.833333 
1 1:-0.722222 2:0.166667 3:-0.694915 4:-0.916667

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