The ANN we have referred to so far is called a feed-forward neural network since the connections between the units and layers do not form a cycle and move only in one direction (from the input layer to the output layer).
Let's implement the feed-forward neural network example with simple Spark ML code:
object FeedForwardNetworkWithSpark { def main(args:Array[String]): Unit ={ val recordReader:RecordReader = new CSVRecordReader(0,",") val conf = new SparkConf() .setMaster("spark://master:7077") .setAppName("FeedForwardNetwork-Iris") val sc = new SparkContext(conf) val numInputs:Int = 4 val outputNum = 3 val iterations =1 val multiLayerConfig:MultiLayerConfiguration = new ...