Scala Machine Learning Projects

Implementing a client subscription assessment model

To predict a client subscription assessment, we use the deep learning classifier implementation from H2O. First, we set up and create a Spark session:

val spark = SparkSession.builder        .master("local[*]")        .config("spark.sql.warehouse.dir", "E:/Exp/") // change accordingly        .appName(s"OneVsRestExample")        .getOrCreate()

Then we load the dataset as a data frame:

spark.sqlContext.setConf("spark.sql.caseSensitive", "false");val trainDF = spark.read.option("inferSchema","true")            .format("com.databricks.spark.csv")            .option("delimiter", ";")            .option("header", "true")            .load("data/bank-additional-full.csv")

Although there are categorical features in this dataset, there is no need to use a StringIndexer ...