在spark.ml中，实现了加速失效时间（AFT）模型，这是一个用于检查数据的参数生存回归模型。 它描述了生存时间对数的模型，因此它通常被称为生存分析的对数线性模型。 不同于为相同目的设计的比例风险模型，AFT模型更容易并行化，因为每个实例独立地贡献于目标函数。
当在具有常量非零列的数据集上匹配AFTSurvivalRegressionModel而没有截距时，Spark MLlib为常量非零列输出零系数。 这种行为不同于R survival :: survreg。
导入包
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.Dataset
import org.apache.spark.sql.Row
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.functions._
import org.apache.spark.ml.linalg.Vectors
import org.apache.spark.ml.feature.VectorAssembler
import org.apache.spark.ml.Pipeline
import org.apache.spark.ml.evaluation.RegressionEvaluator
import org.apache.spark.ml.regression.AFTSurvivalRegression
import org.apache.spark.ml.tuning.{ CrossValidator, ParamGridBuilder }
导入样本数据
val spark = SparkSession.builder().appName("Spark Survival regression").config("spark.some.config.option", "some-value").getOrCreate()
// For implicit conversions like converting RDDs to DataFrames
import spark.implicits._
val dataList: List[(Double, Double, Double, Double,Double, Double, Double, Double,Double, Double)] = List(
(16, 1, 1, 0, 0, 1, 24, 82, 14, 0),
(1, 1, 1, 0, 1, 0, 26, 85, 12, 0),
(4, 0, 1, 0, 0, 0, 25, 85, 12, 0),
(3, 1, 1, 0, 1, 1, 21, 85, 9, 0),
(36, 1, 1, 0, 1, 0, 22, 82, 12, 0),
(36, 1, 1, 0, 0, 0, 18, 82, 11, 0),
(16, 1, 1, 1, 1, 0, 20, 81, 9, 0),
(8, 0, 1, 0, 1, 0, 24, 85, 12, 0),
(20, 1, 1, 1, 0, 0, 24, 85, 12, 0),
(44, 1, 1, 0, 0, 0, 24, 82, 14, 0),
(20, 1, 1, 0, 1, 0, 26, 84, 12, 0),
(30, 1, 1, 0, 1, 0, 22, 84, 12, 1),
(24, 1, 1, 0, 0, 0, 19, 83, 12, 0),
(13, 1, 1, 0, 0, 0, 22, 80, 14, 0),
(6, 1, 1, 0, 0, 0, 27, 84, 16, 0),
(2, 1, 1, 0, 0, 0, 22, 81, 12, 1),
(5, 1, 1, 0, 0, 0, 26, 85, 13, 0),
(192, 1, 1, 0, 0, 0, 21, 78, 12, 0),
(4, 1, 1, 0, 0, 0, 20, 83, 12, 0),
(12, 1, 1, 0, 1, 0, 22, 81, 12, 0),
(4, 1, 2, 0, 0, 0, 24, 86, 12, 0),
(16, 0, 2, 1, 1, 1, 21, 84, 12, 1),
(24, 1, 1, 0, 0, 0, 27, 84, 14, 0),
(16, 1, 1, 0, 1, 0, 23, 81, 12, 0),
(3, 1, 1, 0, 0, 0, 26, 84, 14, 0),
(16, 1, 1, 0, 1, 0, 24, 82, 14, 0),
(28, 1, 1, 0, 0, 0, 23, 81, 12, 0),
(1, 1, 1, 0, 1, 0, 19, 81, 12, 0),
(13, 1, 1, 0, 0, 1, 23, 85, 14, 0),
(36, 1, 1, 0, 0, 0, 21, 83, 10, 0),
(32, 1, 1, 0, 1, 0, 20, 82, 12, 1),
(16, 1, 1, 0, 1, 1, 21, 80, 12, 0),
(2, 1, 1, 0, 0, 1, 21, 83, 12, 0),
(8, 1, 1, 0, 0, 1, 24, 83, 14, 1),
(1, 1, 1, 0, 0, 0, 22, 83, 10, 0),
(24, 1, 2, 0, 0, 0, 18, 79, 11, 0),
(64, 1, 1, 0, 1, 0, 20, 84, 12, 0),
(8, 1, 1, 0, 0, 0, 23, 84, 10, 1),
(2, 1, 1, 0, 0, 0, 16, 80, 9, 1),
(12, 1, 1, 0, 0, 0, 22, 80, 13, 0),
(18, 1, 1, 0, 0, 0, 24, 83, 12, 0),
(32, 1, 1, 0, 0, 0, 24, 85, 14, 0),
(2, 1, 1, 0, 0, 0, 19, 78, 12, 0),
(7, 1, 1, 0, 0, 0, 26, 85, 16, 0),
(5, 1, 1, 0, 0, 0, 22, 81, 12, 0),
(44, 1, 1, 0, 0, 0, 22, 82, 16, 0),
(2, 1, 1, 1, 1, 0, 21, 81, 12, 1),
(4, 1, 1, 0, 1, 0, 18, 81, 10, 1),
(2, 0, 1, 0, 0, 0, 21, 86, 12, 1),
(6, 1, 1, 0, 0, 0, 25, 85, 16, 0),
(4, 1, 1, 0, 0, 0, 22, 81, 12, 0),
(36, 1, 1, 0, 0, 0, 24, 83, 12, 0),
(12, 1, 1, 0, 0, 0, 22, 83, 13, 1),
(24, 1, 1, 0, 0, 0, 20, 85, 12, 0),
(42, 1, 1, 0, 0, 0, 25, 82, 16, 0),
(16, 1, 1, 0, 1, 0, 21, 79, 13, 0),
(44, 1, 1, 0, 0, 0, 25, 84, 12, 0),
(44, 1, 1, 0, 0, 0, 26, 84, 16, 0),
(10, 1, 1, 0, 0, 0, 22, 83, 12, 0),
(4, 1, 1, 1, 0, 0, 20, 81, 11, 0),
(12, 1, 1, 0, 1, 0, 26, 84, 12, 0),
(28, 1, 1, 0, 0, 0, 22, 82, 12, 0),
(24, 1, 1, 0, 0, 0, 18, 82, 11, 0),
(6, 1, 1, 0, 1, 0, 19, 78, 11, 0),
(28, 1, 1, 0, 0, 0, 21, 83, 12, 0),
(12, 1, 1, 1, 1, 0, 21, 81, 12, 0),
(34, 1, 1, 0, 0, 0, 24, 82, 12, 0),
(2, 1, 1, 0, 0, 0, 21, 84, 13, 0),
(48, 1, 1, 0, 0, 0, 21, 84, 14, 0),
(16, 1, 1, 0, 0, 0, 20, 80, 12, 0),
(26, 1, 1, 0, 0, 0, 26, 84, 12, 1),
(6, 1, 1, 0, 1, 0, 24, 84, 14, 0),
(2, 1, 3, 0, 0, 0, 22, 85, 12, 1),
(24, 1, 1, 0, 0, 0, 24, 85, 12, 0),
(6, 1, 1, 0, 0, 0, 23, 83, 12, 0),
(16, 1, 1, 0, 1, 0, 28, 85, 16, 0),
(16, 1, 1, 1, 0, 0, 20, 80, 12, 0),
(8, 1, 1, 0, 1, 0, 21, 84, 12, 0),
(28, 1, 1, 0, 0, 0, 23, 85, 14, 0),
(7, 1, 1, 0, 0, 0, 24, 83, 15, 0),
(5, 1, 1, 1, 1, 0, 19, 82, 8, 0),
(18, 1, 1, 0, 1, 0, 22, 80, 12, 0),
(4, 1, 1, 0, 1, 0, 19, 82, 12, 1),
(18, 1, 1, 0, 0, 0, 19, 83, 12, 0),
(6, 1, 2, 0, 0, 0, 19, 83, 12, 0),
(1, 1, 1, 1, 1, 0, 20, 84, 8, 1),
(10, 1, 1, 1, 1, 1, 17, 78, 8, 0),
(1, 1, 1, 0, 1, 0, 23, 81, 13, 0),
(1, 1, 1, 0, 0, 0, 17, 81, 11, 0),
(12, 1, 3, 0, 0, 0, 22, 81, 12, 0),
(12, 1, 3, 0, 0, 0, 23, 85, 14, 0),
(40, 1, 1, 0, 0, 0, 25, 83, 12, 0),
(12, 1, 1, 0, 1, 0, 22, 83, 12, 0),
(14, 1, 1, 0, 1, 0, 17, 79, 11, 0),
(52, 1, 1, 0, 1, 0, 21, 81, 12, 0),
(5, 1, 1, 0, 1, 0, 16, 78, 10, 0),
(3, 1, 1, 0, 1, 0, 19, 83, 12, 0),
(28, 1, 1, 0, 0, 0, 19, 80, 10, 0),
(16, 1, 1, 0, 1, 0, 20, 82, 12, 1),
(8, 1, 1, 0, 0, 0, 25, 86, 16, 0),
(4, 1, 1, 1, 1, 0, 20, 85, 10, 0),
(13, 1, 1, 0, 0, 0, 25, 84, 12, 0),
(20, 1, 1, 0, 1, 0, 18, 78, 10, 0),
(12, 1, 1, 0, 0, 0, 21, 79, 12, 0),
(4, 1, 1, 0, 0, 0, 22, 84, 12, 0),
(52, 1, 1, 0, 1, 0, 20, 80, 12, 1),
(23, 0, 1, 0, 0, 0, 27, 84, 12, 0),
(16, 1, 3, 1, 0, 0, 17, 79, 9, 1),
(4, 0, 1, 0, 1, 0, 23, 85, 13, 0),
(6, 1, 1, 0, 0, 1, 26, 85, 12, 0),
(4, 1, 1, 0, 0, 0, 22, 85, 12, 0),
(1, 1, 1, 0, 0, 0, 25, 84, 13, 0),
(16, 1, 1, 0, 0, 0, 18, 81, 12, 0),
(18, 1, 2, 0, 1, 0, 20, 81, 14, 0),
(3, 1, 1, 0, 0, 0, 23, 85, 12, 0),
(16, 1, 1, 0, 0, 0, 24, 85, 14, 1),
(96, 1, 1, 0, 0, 0, 21, 80, 13, 0),
(24, 1, 3, 0, 0, 0, 19, 83, 9, 0),
(48, 1, 2, 0, 1, 0, 18, 79, 12, 0),
(4, 1, 1, 0, 0, 0, 19, 83, 11, 0),
(2, 1, 3, 0, 0, 0, 18, 82, 12, 1),
(16, 1, 1, 0, 1, 1, 19, 79, 11, 0),
(28, 1, 1, 0, 0, 0, 19, 82, 12, 0),
(1, 1, 1, 0, 0, 0, 23, 85, 12, 0),
(52, 1, 1, 0, 0, 0, 23, 82, 14, 0),
(32, 1, 2, 1, 0, 0, 20, 82, 14, 0),
(20, 1, 3, 0, 0, 0, 20, 82, 12, 0),
(12, 1, 3, 0, 0, 0, 20, 85, 12, 0),
(8, 1, 3, 0, 0, 0, 17, 78, 11, 0),
(36, 1, 1, 0, 0, 0, 24, 81, 16, 0),
(8, 1, 1, 0, 0, 0, 24, 85, 12, 1),
(24, 1, 1, 0, 0, 0, 20, 83, 11, 1),
(36, 1, 1, 0, 0, 0, 24, 83, 16, 0),
(16, 1, 1, 0, 0, 0, 24, 84, 12, 0),
(3, 1, 1, 0, 1, 0, 22, 80, 12, 0),
(32, 1, 1, 0, 0, 0, 22, 80, 15, 0),
(16, 1, 1, 0, 0, 0, 22, 84, 12, 0),
(48, 1, 1, 0, 0, 0, 23, 85, 16, 0),
(1, 1, 1, 0, 0, 0, 21, 80, 12, 0),
(36, 1, 1, 0, 1, 0, 25, 84, 12, 1),
(30, 1, 1, 0, 0, 0, 24, 81, 12, 0),
(2, 1, 1, 0, 0, 0, 19, 78, 12, 0),
(52, 1, 1, 0, 0, 0, 20, 79, 13, 0),
(36, 1, 1, 1, 0, 1, 21, 83, 13, 0),
(28, 1, 1, 0, 0, 0, 23, 82, 12, 1),
(48, 1, 1, 0, 0, 0, 21, 80, 16, 0),
(16, 1, 3, 0, 1, 0, 19, 78, 7, 0),
(4, 1, 1, 0, 0, 0, 25, 83, 12, 0),
(1, 1, 1, 0, 0, 0, 25, 85, 12, 0),
(6, 1, 1, 0, 0, 0, 20, 82, 12, 1),
(12, 1, 1, 0, 0, 0, 20, 78, 12, 0),
(24, 1, 1, 0, 1, 0, 19, 80, 11, 0),
(40, 1, 1, 1, 0, 0, 22, 80, 10, 0),
(8, 1, 1, 1, 0, 0, 26, 85, 19, 0),
(4, 1, 1, 0, 1, 0, 22, 82, 12, 0),
(20, 1, 2, 0, 0, 0, 23, 84, 12, 0),
(6, 1, 2, 0, 0, 0, 19, 83, 12, 0),
(12, 1, 1, 0, 0, 0, 21, 82, 12, 0),
(8, 1, 1, 1, 0, 0, 23, 84, 16, 0),
(3, 0, 1, 0, 0, 0, 28, 85, 16, 0),
(12, 1, 1, 0, 0, 1, 25, 85, 16, 0),
(16, 1, 1, 0, 0, 0, 19, 80, 12, 0),
(20, 1, 1, 0, 1, 0, 19, 78, 8, 0),
(12, 1, 2, 0, 1, 0, 18, 79, 12, 0),
(16, 1, 3, 0, 0, 0, 20, 83, 12, 0),
(17, 1, 1, 0, 1, 0, 25, 83, 11, 0),
(60, 1, 3, 0, 0, 0, 19, 80, 11, 1),
(12, 1, 3, 1, 0, 0, 19, 81, 10, 1),
(4, 1, 1, 1, 0, 0, 17, 79, 10, 1),
(16, 1, 1, 0, 0, 0, 21, 81, 14, 0),
(3, 1, 1, 0, 1, 0, 21, 83, 12, 0),
(3, 1, 1, 0, 1, 0, 25, 85, 12, 0),
(16, 1, 1, 0, 0, 0, 19, 82, 12, 0),
(24, 1, 1, 1, 0, 1, 19, 78, 12, 0),
(21, 1, 1, 0, 1, 0, 19, 78, 12, 0),
(32, 1, 1, 0, 0, 0, 20, 81, 12, 0),
(8, 1, 1, 1, 1, 0, 26, 85, 11, 0),
(6, 1, 1, 0, 0, 0, 23, 84, 12, 0),
(16, 1, 1, 0, 1, 0, 17, 82, 11, 0),
(12, 1, 1, 0, 1, 0, 24, 81, 12, 0),
(16, 1, 1, 1, 0, 0, 18, 82, 12, 0),
(16, 1, 1, 1, 1, 0, 28, 85, 12, 0),
(8, 1, 1, 0, 0, 0, 26, 85, 16, 1),
(20, 1, 1, 0, 1, 0, 21, 85, 12, 0),
(40, 1, 1, 0, 0, 0, 22, 83, 12, 0),
(12, 1, 1, 0, 0, 0, 22, 83, 12, 0),
(36, 1, 1, 0, 0, 0, 25, 84, 16, 0),
(18, 1, 1, 0, 0, 0, 20, 82, 13, 0),
(48, 1, 1, 0, 0, 0, 20, 81, 12, 0),
(7, 1, 1, 1, 1, 0, 18, 81, 10, 1),
(1, 1, 1, 0, 0, 0, 25, 85, 12, 0),
(24, 1, 1, 0, 0, 0, 21, 85, 12, 0),
(12, 1, 3, 1, 0, 0, 17, 80, 9, 0),
(36, 1, 3, 1, 0, 0, 17, 82, 8, 0),
(3, 1, 3, 1, 0, 0, 18, 79, 10, 0),
(1, 1, 3, 0, 0, 0, 23, 81, 6, 0),
(5, 1, 3, 0, 0, 0, 20, 83, 10, 0),
(24, 1, 3, 1, 0, 0, 19, 83, 11, 1),
(21, 1, 1, 1, 0, 1, 19, 81, 12, 1),
(1, 1, 1, 0, 1, 0, 17, 78, 11, 0),
(8, 1, 1, 0, 0, 0, 21, 79, 12, 0),
(24, 1, 2, 0, 0, 0, 24, 84, 16, 0),
(68, 1, 1, 1, 0, 0, 20, 80, 12, 0),
(20, 1, 1, 0, 0, 0, 19, 80, 14, 0),
(2, 1, 1, 0, 1, 0, 16, 80, 9, 0),
(12, 1, 1, 0, 0, 0, 25, 84, 12, 0),
(40, 1, 1, 0, 0, 1, 24, 82, 14, 0),
(4, 1, 1, 0, 0, 0, 26, 84, 12, 0),
(1, 1, 1, 0, 0, 1, 25, 85, 12, 0),
(32, 1, 1, 0, 1, 0, 25, 84, 11, 1),
(1, 1, 3, 0, 0, 0, 19, 80, 10, 0),
(6, 1, 1, 0, 0, 0, 24, 81, 16, 0),
(13, 1, 1, 0, 0, 1, 27, 85, 16, 0),
(2, 1, 1, 1, 1, 0, 22, 85, 12, 0),
(50, 1, 2, 0, 0, 0, 19, 83, 11, 1),
(32, 1, 1, 0, 1, 0, 21, 78, 12, 0),
(12, 1, 1, 0, 1, 0, 16, 79, 9, 0),
(2, 1, 2, 0, 0, 0, 22, 79, 12, 0),
(8, 1, 2, 0, 0, 0, 23, 82, 12, 1),
(20, 1, 2, 0, 0, 0, 21, 83, 15, 0),
(12, 1, 1, 0, 0, 0, 26, 85, 12, 0),
(8, 1, 1, 0, 0, 0, 21, 85, 12, 0),
(1, 1, 1, 0, 0, 0, 24, 83, 13, 0),
(16, 1, 1, 0, 1, 0, 21, 83, 11, 0),
(24, 1, 1, 0, 0, 0, 17, 80, 11, 0),
(4, 1, 1, 0, 0, 0, 24, 85, 13, 0),
(22, 1, 2, 0, 0, 0, 25, 83, 12, 0),
(5, 1, 2, 0, 0, 0, 20, 82, 12, 0),
(36, 1, 2, 1, 0, 0, 23, 84, 12, 0),
(12, 1, 1, 0, 0, 0, 23, 80, 12, 0),
(52, 1, 1, 0, 0, 0, 19, 79, 13, 0),
(9, 1, 1, 0, 0, 0, 25, 85, 16, 0),
(6, 1, 1, 0, 0, 0, 22, 85, 14, 0),
(26, 1, 1, 0, 0, 0, 21, 81, 13, 0),
(8, 1, 1, 0, 0, 0, 26, 84, 16, 0),
(18, 0, 1, 1, 0, 0, 23, 84, 14, 0),
(2, 1, 3, 0, 0, 0, 27, 85, 19, 0),
(20, 1, 1, 0, 0, 0, 23, 82, 16, 0),
(16, 1, 1, 0, 0, 0, 25, 85, 14, 1),
(2, 0, 1, 0, 0, 0, 22, 86, 12, 0),
(48, 1, 1, 0, 0, 1, 20, 80, 12, 1),
(4, 1, 1, 0, 1, 0, 23, 83, 11, 0),
(8, 1, 1, 0, 0, 0, 22, 80, 12, 0),
(40, 1, 1, 0, 1, 0, 19, 81, 12, 1),
(14, 0, 1, 0, 0, 0, 27, 85, 19, 0),
(80, 1, 1, 0, 0, 0, 25, 83, 16, 0),
(13, 0, 1, 0, 0, 0, 24, 85, 16, 0),
(20, 1, 1, 0, 1, 0, 26, 84, 16, 1),
(44, 1, 1, 0, 0, 0, 18, 78, 12, 0),
(12, 1, 1, 0, 0, 0, 20, 84, 13, 0),
(20, 1, 1, 0, 0, 0, 22, 79, 14, 0),
(32, 1, 1, 0, 0, 0, 24, 84, 12, 1),
(2, 1, 1, 0, 0, 0, 23, 83, 12, 0),
(28, 1, 2, 0, 0, 0, 22, 85, 14, 1),
(6, 1, 2, 0, 0, 0, 21, 84, 12, 0),
(6, 1, 1, 0, 1, 0, 26, 83, 12, 0),
(38, 1, 1, 0, 0, 0, 22, 81, 12, 0),
(16, 1, 1, 0, 1, 0, 21, 80, 14, 0),
(1, 1, 1, 0, 0, 0, 26, 85, 12, 0),
(7, 1, 1, 0, 0, 0, 26, 84, 12, 0),
(10, 1, 1, 0, 1, 0, 23, 83, 12, 0),
(3, 1, 1, 0, 0, 0, 23, 82, 16, 0),
(36, 1, 1, 0, 0, 0, 21, 83, 12, 0),
(12, 1, 1, 0, 0, 0, 20, 85, 12, 0),
(8, 1, 2, 1, 0, 0, 19, 81, 11, 1),
(14, 1, 1, 0, 0, 0, 22, 81, 12, 0),
(4, 1, 1, 0, 1, 1, 20, 79, 11, 1),
(1, 1, 1, 0, 1, 0, 22, 83, 12, 0),
(2, 1, 1, 0, 0, 0, 24, 85, 13, 1),
(1, 1, 1, 0, 1, 1, 21, 83, 12, 0),
(4, 1, 1, 0, 0, 0, 24, 85, 12, 0),
(24, 1, 1, 1, 0, 0, 22, 79, 14, 0),
(12, 1, 1, 0, 0, 0, 23, 80, 15, 0),
(12, 1, 1, 0, 1, 0, 21, 79, 12, 0),
(20, 1, 1, 0, 0, 0, 26, 84, 12, 0),
(7, 1, 1, 0, 0, 0, 21, 84, 12, 0),
(12, 1, 1, 0, 1, 0, 17, 80, 10, 0),
(8, 1, 1, 0, 1, 0, 16, 78, 9, 0),
(6, 1, 1, 0, 1, 0, 19, 81, 11, 0),
(16, 1, 1, 0, 0, 1, 23, 84, 15, 0),
(48, 1, 1, 0, 0, 0, 20, 79, 13, 0),
(2, 1, 1, 0, 0, 0, 22, 85, 12, 0),
(1, 1, 1, 0, 0, 0, 22, 84, 12, 0),
(16, 1, 1, 1, 1, 0, 18, 80, 11, 1),
(8, 1, 1, 0, 0, 0, 21, 85, 14, 0),
(24, 1, 1, 0, 0, 0, 23, 83, 15, 0),
(4, 1, 1, 0, 0, 0, 20, 80, 12, 0),
(2, 1, 2, 0, 0, 0, 23, 83, 12, 0),
(5, 0, 1, 0, 0, 0, 27, 85, 16, 0),
(24, 1, 2, 1, 0, 0, 20, 79, 12, 0),
(1, 1, 2, 1, 0, 0, 18, 82, 11, 0),
(12, 1, 1, 0, 0, 0, 21, 78, 13, 0),
(10, 1, 1, 1, 0, 0, 19, 81, 12, 0),
(48, 1, 1, 0, 0, 0, 21, 81, 11, 0),
(24, 1, 1, 0, 0, 0, 21, 84, 13, 0),
(56, 1, 1, 0, 0, 0, 25, 83, 13, 0),
(52, 1, 1, 0, 0, 0, 21, 79, 12, 0),
(6, 1, 1, 0, 1, 0, 19, 79, 10, 0),
(32, 1, 1, 1, 0, 0, 17, 81, 10, 0),
(8, 1, 1, 0, 1, 0, 22, 84, 12, 1),
(6, 1, 1, 0, 0, 0, 17, 81, 10, 0),
(24, 1, 1, 1, 1, 0, 18, 81, 11, 0),
(2, 1, 3, 0, 0, 0, 19, 79, 12, 0),
(20, 1, 3, 0, 0, 0, 23, 84, 12, 0),
(40, 1, 2, 1, 1, 0, 23, 80, 12, 0),
(4, 1, 2, 0, 0, 0, 20, 82, 12, 1),
(3, 0, 1, 0, 1, 0, 24, 86, 11, 1),
(24, 1, 1, 0, 1, 0, 19, 78, 9, 1),
(8, 1, 1, 0, 0, 0, 20, 84, 12, 0),
(24, 1, 1, 0, 0, 0, 21, 82, 12, 0),
(36, 1, 1, 0, 0, 0, 19, 83, 12, 0),
(1, 1, 1, 0, 1, 0, 21, 80, 12, 1),
(8, 1, 1, 0, 0, 0, 19, 78, 12, 0),
(8, 1, 1, 0, 1, 0, 23, 81, 12, 0),
(40, 1, 1, 0, 0, 0, 20, 84, 12, 0),
(5, 1, 1, 0, 0, 0, 16, 79, 9, 1),
(24, 1, 1, 0, 0, 0, 23, 85, 16, 0),
(2, 1, 3, 0, 0, 0, 21, 83, 12, 0),
(6, 0, 1, 0, 0, 0, 26, 85, 12, 0),
(24, 1, 1, 0, 0, 0, 22, 80, 14, 0),
(42, 1, 1, 0, 1, 0, 21, 84, 11, 0),
(12, 1, 1, 0, 0, 0, 16, 79, 10, 0),
(48, 1, 2, 0, 0, 0, 19, 80, 12, 0),
(12, 1, 1, 0, 0, 1, 20, 83, 10, 0),
(7, 1, 3, 0, 0, 0, 23, 81, 12, 1),
(10, 1, 1, 0, 1, 0, 24, 84, 12, 0),
(1, 1, 1, 0, 0, 0, 21, 78, 12, 0),
(2, 1, 1, 0, 0, 0, 23, 85, 12, 1),
(3, 1, 1, 0, 0, 0, 21, 85, 12, 0),
(6, 1, 1, 0, 1, 0, 19, 80, 11, 0),
(40, 1, 1, 0, 1, 0, 20, 79, 12, 0),
(38, 1, 1, 0, 0, 0, 22, 80, 12, 0),
(1, 1, 1, 0, 0, 0, 18, 79, 11, 0),
(2, 1, 1, 0, 1, 0, 19, 81, 10, 1),
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(56, 1, 2, 1, 0, 0, 17, 80, 11, 0),
(4, 1, 2, 0, 0, 0, 20, 84, 12, 0),
(6, 1, 1, 1, 0, 0, 19, 81, 10, 1),
(2, 1, 2, 1, 0, 0, 21, 81, 14, 0),
(8, 1, 1, 0, 0, 0, 21, 84, 14, 0),
(14, 1, 2, 0, 0, 0, 22, 82, 13, 0),
(8, 1, 3, 0, 0, 0, 19, 83, 10, 0),
(1, 1, 3, 0, 0, 0, 24, 85, 9, 0),
(2, 1, 3, 0, 0, 0, 19, 83, 11, 1),
(16, 0, 1, 0, 0, 1, 27, 84, 16, 1),
(8, 1, 1, 0, 0, 0, 26, 84, 16, 0),
(48, 1, 1, 1, 1, 1, 18, 80, 8, 0),
(52, 1, 1, 1, 1, 0, 17, 81, 7, 0),
(25, 1, 1, 1, 1, 0, 21, 82, 11, 0),
(20, 1, 1, 1, 1, 0, 22, 83, 12, 0),
(12, 1, 1, 1, 1, 0, 19, 81, 11, 1),
(8, 1, 3, 0, 0, 0, 23, 83, 14, 0),
(5, 1, 3, 1, 1, 1, 20, 81, 10, 1),
(4, 1, 1, 0, 1, 1, 25, 84, 16, 0),
(16, 1, 1, 0, 0, 0, 25, 84, 16, 0),
(1, 1, 1, 0, 0, 0, 22, 81, 15, 0),
(5, 1, 1, 0, 1, 0, 26, 85, 16, 0),
(3, 1, 1, 1, 1, 0, 19, 83, 11, 0),
(46, 1, 1, 1, 1, 0, 20, 78, 12, 0),
(8, 1, 3, 1, 0, 0, 18, 78, 12, 0),
(40, 1, 1, 0, 0, 0, 18, 80, 10, 0),
(1, 1, 3, 1, 1, 1, 22, 82, 12, 0),
(4, 1, 2, 0, 0, 1, 24, 86, 13, 0),
(3, 1, 1, 0, 1, 0, 22, 81, 12, 0),
(2, 1, 3, 0, 0, 1, 25, 84, 12, 0),
(2, 1, 1, 0, 0, 0, 27, 85, 15, 0),
(3, 1, 1, 0, 0, 0, 22, 80, 16, 0),
(46, 1, 1, 0, 0, 0, 25, 83, 14, 0),
(2, 1, 3, 0, 0, 0, 19, 81, 12, 1),
(36, 1, 1, 0, 0, 0, 21, 82, 12, 0),
(6, 0, 3, 0, 0, 0, 22, 85, 12, 0),
(8, 1, 1, 0, 0, 0, 18, 81, 11, 0),
(16, 1, 1, 0, 0, 0, 19, 79, 12, 0),
(16, 1, 1, 1, 1, 0, 19, 78, 9, 0),
(12, 1, 3, 1, 0, 0, 23, 80, 9, 1),
(6, 1, 2, 1, 0, 0, 20, 83, 13, 0),
(5, 0, 3, 0, 0, 0, 21, 85, 14, 0),
(16, 1, 3, 1, 1, 0, 19, 84, 11, 0),
(12, 1, 3, 0, 0, 0, 19, 81, 12, 0),
(1, 1, 3, 0, 0, 0, 26, 85, 11, 0),
(4, 1, 1, 1, 1, 0, 21, 78, 12, 0),
(24, 1, 1, 1, 0, 0, 19, 78, 11, 0),
(1, 1, 1, 0, 0, 0, 22, 80, 12, 0),
(10, 1, 3, 0, 1, 1, 22, 81, 13, 0),
(10, 1, 1, 0, 0, 0, 25, 85, 13, 0),
(2, 1, 3, 1, 0, 0, 20, 84, 12, 1),
(2, 1, 3, 0, 1, 1, 24, 84, 12, 0),
(64, 1, 3, 1, 0, 0, 21, 80, 11, 0),
(8, 1, 2, 1, 0, 0, 21, 84, 12, 0),
(48, 1, 2, 1, 1, 0, 21, 81, 12, 0),
(28, 1, 3, 0, 0, 0, 21, 80, 11, 1),
(24, 1, 3, 0, 0, 0, 18, 79, 10, 0),
(18, 1, 2, 1, 0, 0, 23, 82, 11, 0),
(6, 1, 3, 0, 0, 0, 21, 85, 12, 0),
(3, 1, 2, 1, 1, 0, 19, 82, 11, 1),
(56, 1, 3, 0, 0, 0, 26, 84, 15, 1),
(18, 1, 1, 0, 0, 0, 24, 83, 13, 0),
(2, 1, 3, 0, 0, 0, 21, 81, 9, 0),
(6, 1, 3, 0, 0, 0, 20, 79, 6, 1),
(12, 1, 3, 0, 0, 0, 24, 82, 14, 0),
(32, 1, 1, 0, 1, 0, 19, 82, 9, 0),
(3, 1, 3, 0, 0, 0, 21, 83, 12, 1),
(72, 1, 1, 0, 0, 0, 19, 83, 11, 0),
(5, 1, 1, 1, 1, 0, 19, 84, 7, 0),
(12, 1, 2, 0, 0, 0, 20, 80, 13, 1),
(8, 1, 3, 0, 0, 0, 23, 82, 12, 0),
(8, 1, 1, 0, 1, 0, 23, 81, 13, 0),
(16, 1, 1, 0, 1, 0, 21, 78, 14, 0),
(2, 0, 1, 0, 0, 0, 26, 85, 13, 0),
(3, 0, 1, 0, 0, 0, 27, 85, 16, 0),
(12, 1, 2, 1, 0, 0, 17, 79, 10, 0),
(40, 1, 2, 1, 0, 0, 18, 81, 12, 0),
(96, 1, 1, 0, 0, 0, 25, 83, 14, 0),
(4, 1, 1, 0, 1, 1, 22, 81, 12, 0),
(3, 1, 1, 0, 1, 0, 20, 84, 12, 1),
(12, 1, 1, 0, 0, 0, 25, 83, 16, 0),
(28, 1, 1, 0, 1, 0, 25, 83, 16, 0),
(7, 1, 1, 1, 1, 1, 22, 84, 11, 0),
(1, 1, 2, 1, 0, 0, 22, 85, 15, 0),
(1, 1, 1, 0, 1, 0, 23, 83, 14, 0),
(4, 1, 3, 0, 0, 0, 26, 83, 9, 0),
(3, 1, 3, 0, 0, 0, 25, 84, 14, 1),
(12, 1, 3, 1, 0, 0, 24, 84, 12, 0),
(1, 1, 2, 0, 0, 0, 19, 83, 12, 0),
(14, 1, 1, 0, 0, 1, 26, 84, 15, 0),
(12, 1, 1, 0, 0, 0, 20, 79, 12, 0),
(8, 1, 2, 1, 0, 0, 19, 81, 12, 0),
(12, 1, 3, 0, 0, 0, 25, 82, 12, 0),
(1, 1, 3, 0, 0, 0, 22, 85, 11, 0),
(8, 1, 1, 1, 0, 0, 17, 81, 10, 0),
(8, 1, 1, 1, 1, 0, 24, 85, 9, 1),
(8, 1, 1, 1, 1, 0, 15, 80, 9, 0),
(7, 1, 3, 0, 1, 0, 23, 84, 13, 0),
(12, 1, 3, 0, 0, 0, 21, 82, 12, 0),
(6, 1, 3, 0, 0, 0, 24, 84, 12, 0),
(2, 1, 2, 0, 0, 0, 23, 85, 14, 0),
(16, 1, 3, 1, 0, 0, 20, 81, 11, 1),
(24, 1, 1, 0, 0, 0, 18, 80, 9, 1),
(24, 1, 3, 0, 0, 0, 20, 79, 10, 0),
(12, 1, 3, 0, 1, 1, 24, 83, 9, 0),
(72, 1, 1, 1, 0, 0, 16, 81, 9, 1),
(6, 1, 1, 0, 1, 0, 23, 83, 12, 0),
(1, 1, 2, 0, 0, 0, 25, 82, 13, 0),
(48, 1, 1, 0, 0, 0, 20, 80, 12, 0),
(3, 1, 1, 0, 1, 0, 22, 83, 12, 0),
(24, 1, 1, 0, 0, 0, 23, 81, 12, 0),
(12, 1, 1, 0, 0, 0, 23, 82, 12, 0),
(26, 1, 1, 0, 0, 0, 22, 80, 12, 0),
(3, 1, 1, 0, 1, 0, 23, 83, 12, 0),
(24, 1, 1, 0, 0, 0, 20, 80, 12, 0),
(1, 1, 1, 0, 0, 1, 20, 78, 12, 0),
(5, 1, 1, 0, 1, 0, 24, 83, 12, 0),
(2, 1, 1, 0, 1, 0, 21, 79, 12, 0),
(12, 1, 1, 0, 0, 0, 19, 80, 12, 0),
(48, 1, 1, 0, 0, 0, 23, 81, 12, 0),
(3, 1, 2, 0, 1, 1, 23, 81, 13, 0),
(4, 1, 1, 0, 1, 0, 22, 81, 12, 0),
(6, 1, 1, 0, 1, 0, 22, 81, 12, 0),
(4, 1, 1, 0, 1, 1, 24, 82, 13, 0),
(52, 1, 1, 1, 0, 0, 22, 81, 12, 0),
(8, 1, 2, 1, 0, 0, 23, 81, 12, 0),
(20, 1, 1, 1, 0, 0, 21, 81, 12, 0),
(20, 1, 1, 0, 0, 0, 23, 82, 12, 0),
(28, 1, 1, 0, 0, 0, 22, 83, 12, 0),
(4, 1, 1, 0, 0, 0, 24, 82, 12, 1),
(16, 1, 1, 1, 0, 0, 19, 78, 12, 0),
(8, 1, 2, 0, 0, 0, 19, 79, 12, 0),
(5, 1, 1, 0, 0, 0, 21, 80, 12, 0),
(11, 1, 1, 0, 1, 0, 24, 83, 12, 0),
(4, 1, 2, 0, 0, 0, 24, 83, 12, 0),
(3, 1, 1, 0, 0, 0, 22, 81, 12, 0),
(2, 1, 1, 0, 0, 0, 23, 81, 12, 0),
(2, 1, 1, 0, 0, 0, 21, 80, 12, 0),
(6, 1, 1, 0, 0, 0, 21, 80, 13, 0),
(8, 1, 1, 1, 1, 0, 21, 79, 12, 0),
(1, 1, 1, 0, 1, 1, 18, 79, 12, 1),
(48, 1, 1, 0, 1, 0, 19, 79, 12, 0),
(32, 1, 1, 0, 0, 0, 20, 79, 13, 0),
(32, 1, 1, 0, 0, 1, 20, 79, 12, 0),
(6, 1, 1, 0, 1, 0, 22, 81, 12, 0),
(6, 1, 1, 0, 0, 0, 25, 82, 12, 0),
(24, 1, 1, 0, 0, 1, 20, 79, 12, 0),
(4, 1, 3, 0, 0, 0, 20, 79, 14, 0),
(16, 1, 1, 0, 0, 0, 22, 82, 12, 0),
(12, 1, 1, 0, 0, 0, 21, 80, 12, 0),
(2, 1, 1, 0, 1, 0, 24, 83, 12, 0),
(1, 1, 1, 0, 0, 0, 21, 81, 12, 0),
(3, 1, 1, 0, 1, 0, 22, 82, 12, 0),
(7, 1, 1, 1, 1, 1, 25, 83, 12, 0),
(56, 1, 1, 0, 0, 0, 24, 81, 12, 0),
(1, 1, 1, 0, 0, 0, 22, 80, 12, 0),
(24, 1, 1, 0, 0, 0, 21, 81, 12, 0),
(16, 1, 1, 0, 1, 0, 19, 78, 12, 0),
(20, 1, 1, 0, 1, 0, 22, 82, 12, 0),
(1, 1, 1, 0, 0, 0, 22, 81, 13, 0),
(120, 1, 3, 0, 0, 0, 22, 80, 12, 0),
(44, 1, 1, 0, 0, 0, 22, 81, 14, 0),
(3, 1, 1, 0, 0, 0, 25, 83, 12, 0),
(32, 1, 1, 0, 0, 0, 20, 80, 12, 0),
(6, 1, 1, 0, 0, 0, 22, 82, 12, 0),
(52, 1, 1, 0, 0, 0, 22, 79, 12, 0),
(24, 1, 2, 0, 0, 1, 23, 81, 12, 0),
(72, 1, 1, 0, 0, 0, 21, 81, 12, 0),
(24, 1, 2, 0, 0, 0, 21, 81, 12, 0),
(3, 1, 1, 0, 1, 0, 22, 82, 10, 0),
(6, 1, 1, 0, 1, 0, 21, 79, 12, 0),
(24, 1, 1, 0, 1, 0, 24, 82, 12, 0),
(16, 1, 2, 0, 0, 0, 23, 83, 12, 0),
(5, 1, 1, 0, 1, 0, 25, 83, 12, 0),
(48, 1, 1, 0, 0, 0, 20, 79, 12, 0),
(10, 1, 1, 0, 1, 0, 23, 82, 12, 0),
(48, 1, 1, 0, 0, 0, 23, 82, 13, 0),
(2, 1, 1, 1, 1, 0, 24, 82, 12, 0),
(6, 1, 1, 0, 0, 0, 24, 82, 14, 0),
(36, 1, 2, 0, 0, 0, 22, 82, 14, 0),
(12, 1, 1, 0, 0, 0, 22, 83, 12, 0),
(2, 1, 1, 0, 1, 0, 21, 85, 12, 0),
(4, 1, 1, 0, 1, 0, 18, 80, 12, 1),
(24, 1, 1, 0, 0, 0, 23, 82, 13, 0),
(1, 1, 1, 0, 0, 0, 23, 83, 11, 0),
(20, 1, 1, 0, 0, 0, 21, 81, 13, 0),
(76, 1, 1, 0, 0, 0, 21, 83, 14, 0),
(8, 1, 1, 0, 0, 0, 20, 79, 12, 0),
(4, 1, 3, 0, 0, 0, 24, 81, 11, 0),
(36, 1, 1, 0, 1, 0, 20, 80, 12, 0),
(6, 1, 1, 0, 0, 0, 21, 82, 12, 0),
(32, 1, 1, 0, 0, 0, 19, 83, 14, 0),
(4, 1, 1, 0, 0, 0, 20, 81, 12, 0),
(4, 1, 1, 0, 1, 0, 21, 79, 12, 0),
(40, 1, 1, 1, 1, 0, 22, 85, 12, 0),
(3, 1, 3, 0, 0, 0, 20, 81, 9, 0),
(8, 1, 1, 1, 0, 1, 23, 83, 10, 1),
(32, 1, 1, 0, 0, 0, 18, 80, 11, 0),
(10, 0, 1, 0, 0, 0, 28, 85, 15, 1),
(1, 1, 1, 0, 0, 0, 20, 84, 12, 1),
(1, 1, 1, 0, 1, 0, 20, 80, 12, 0),
(5, 1, 1, 1, 1, 1, 21, 78, 15, 0),
(24, 1, 1, 0, 1, 0, 18, 81, 10, 0),
(48, 1, 1, 0, 0, 0, 23, 83, 12, 0),
(12, 1, 1, 0, 1, 0, 24, 83, 12, 0),
(20, 1, 1, 0, 0, 0, 27, 85, 17, 0),
(4, 1, 1, 0, 1, 0, 21, 84, 12, 0),
(16, 1, 1, 1, 1, 0, 21, 82, 12, 0),
(32, 1, 3, 1, 0, 0, 18, 82, 10, 1),
(24, 1, 1, 0, 0, 0, 26, 85, 14, 1),
(13, 1, 1, 0, 0, 0, 21, 82, 12, 0),
(1, 1, 1, 1, 0, 0, 16, 81, 9, 1),
(16, 1, 1, 0, 1, 0, 20, 81, 12, 0),
(44, 1, 1, 0, 0, 0, 21, 80, 12, 0),
(32, 1, 1, 0, 1, 1, 22, 83, 12, 0),
(1, 1, 1, 0, 1, 1, 20, 83, 12, 0),
(8, 1, 1, 0, 1, 0, 22, 79, 12, 0),
(6, 1, 1, 0, 0, 0, 22, 82, 13, 1),
(6, 1, 1, 1, 1, 0, 21, 81, 12, 0),
(32, 1, 1, 0, 0, 1, 25, 84, 18, 0),
(28, 1, 1, 0, 1, 1, 19, 80, 12, 0),
(7, 1, 1, 0, 0, 1, 24, 83, 14, 0),
(12, 1, 1, 1, 1, 1, 20, 80, 10, 1),
(4, 1, 1, 1, 0, 0, 18, 81, 11, 0),
(32, 1, 1, 0, 0, 0, 23, 81, 16, 0),
(48, 1, 1, 1, 0, 0, 20, 84, 11, 1),
(32, 1, 1, 1, 0, 0, 17, 78, 12, 1),
(3, 1, 2, 0, 1, 0, 19, 79, 11, 1),
(4, 1, 2, 0, 0, 0, 21, 78, 12, 0),
(4, 1, 1, 0, 1, 0, 23, 82, 12, 0),
(2, 1, 1, 0, 0, 0, 24, 82, 13, 0),
(3, 1, 1, 0, 0, 1, 21, 80, 12, 0),
(1, 1, 1, 0, 1, 1, 20, 81, 12, 0),
(32, 1, 1, 0, 1, 0, 24, 81, 12, 0),
(24, 1, 1, 0, 0, 0, 20, 80, 12, 0),
(4, 1, 1, 0, 0, 0, 20, 79, 12, 0),
(5, 1, 1, 0, 0, 1, 22, 81, 12, 0),
(24, 1, 2, 0, 0, 0, 21, 80, 12, 0),
(6, 1, 1, 0, 1, 0, 20, 80, 12, 0))
val data = dataList.toDF("label", "censor","race","poverty","smoke","alcohol","agemth","ybirth","yschool","pc3mth").orderBy("label")
建模并调优
val colArray = Array("race", "poverty", "smoke", "alcohol", "agemth", "ybirth", "yschool", "pc3mth")
val assembler = new VectorAssembler().setInputCols(colArray).setOutputCol("features")
val vecDF: DataFrame = assembler.transform(data)
val Array(trainingDF, testDF) = vecDF.randomSplit(Array(0.7, 0.3))
//###########################
// 建立生存回归模型
val AFT = new AFTSurvivalRegression().setFeaturesCol("features").setLabelCol("label").setCensorCol("censor").fit(trainingDF)
// 设置管道
val pipeline = new Pipeline().setStages(Array(AFT))
// 设置参数网格
val paramGrid = new ParamGridBuilder().addGrid(AFT.maxIter, Array(100, 500, 1000)).addGrid(AFT.tol, Array(1E-2, 1E-6)).build()
// 选择(prediction, true label)，计算测试误差。
// 注意RegEvaluator.isLargerBetter，评估的度量值是大的好，还是小的好，系统会自动识别
val RegEvaluator = new RegressionEvaluator().setLabelCol(AFT.getLabelCol).setPredictionCol(AFT.getPredictionCol).setMetricName("rmse")
// 设置交叉验证
val cv = new CrossValidator().setEstimator(pipeline).setEvaluator(RegEvaluator).setEstimatorParamMaps(paramGrid).setNumFolds(3)
// 执行交叉验证，并选择出最好的参数集
val cvModel = cv.fit(trainingDF)
// 查看全部参数
cvModel.extractParamMap()
// cvModel.avgMetrics.length=cvModel.getEstimatorParamMaps.length
// cvModel.avgMetrics与cvModel.getEstimatorParamMaps中的元素一一对应
cvModel.avgMetrics.length
cvModel.avgMetrics // 参数对应的平均度量
cvModel.getEstimatorParamMaps.length
cvModel.getEstimatorParamMaps // 参数组合的集合
cvModel.getEvaluator.extractParamMap() // 评估的参数
cvModel.getEvaluator.isLargerBetter // 评估的度量值是大的好，还是小的好
cvModel.getNumFolds // 交叉验证的折数
//################################
// 测试模型
val predictDF: DataFrame = cvModel.transform(testDF).selectExpr(
//"race","poverty","smoke","alcohol","agemth","ybirth","yschool","pc3mth", "features",
"label", "censor",
"round(prediction,2) as prediction").orderBy("label")
predictDF.show
spark.stop()
代码执行结果
// 查看全部参数
cvModel.extractParamMap()
res2: org.apache.spark.ml.param.ParamMap =
{
cv_baf8c9af33b7-estimator: pipeline_20ba567066f7,
cv_baf8c9af33b7-estimatorParamMaps: [Lorg.apache.spark.ml.param.ParamMap;@412a07c8,
cv_baf8c9af33b7-evaluator: regEval_59075079f1c9,
cv_baf8c9af33b7-numFolds: 3,
cv_baf8c9af33b7-seed: -1191137437
}
// cvModel.avgMetrics.length=cvModel.getEstimatorParamMaps.length
// cvModel.avgMetrics与cvModel.getEstimatorParamMaps中的元素一一对应
cvModel.avgMetrics.length
res3: Int = 6
cvModel.avgMetrics // 参数对应的平均度量
res4: Array[Double] = Array(18.53, 17.53, 19.53, 17.63, 18.53, 18.93)
cvModel.getEstimatorParamMaps.length
res5: Int = 6
cvModel.getEstimatorParamMaps // 参数组合的集合
res6: Array[org.apache.spark.ml.param.ParamMap] =
Array({
aftSurvReg_a7e5bc450599-maxIter: 100,
aftSurvReg_a7e5bc450599-tol: 0.01
}, {
aftSurvReg_a7e5bc450599-maxIter: 100,
aftSurvReg_a7e5bc450599-tol: 1.0E-6
}, {
aftSurvReg_a7e5bc450599-maxIter: 500,
aftSurvReg_a7e5bc450599-tol: 0.01
}, {
aftSurvReg_a7e5bc450599-maxIter: 500,
aftSurvReg_a7e5bc450599-tol: 1.0E-6
}, {
aftSurvReg_a7e5bc450599-maxIter: 1000,
aftSurvReg_a7e5bc450599-tol: 0.01
}, {
aftSurvReg_a7e5bc450599-maxIter: 1000,
aftSurvReg_a7e5bc450599-tol: 1.0E-6
})
cvModel.getEvaluator.extractParamMap() // 评估的参数
res7: org.apache.spark.ml.param.ParamMap =
{
regEval_59075079f1c9-labelCol: label,
regEval_59075079f1c9-metricName: rmse,
regEval_59075079f1c9-predictionCol: prediction
}
cvModel.getEvaluator.isLargerBetter // 评估的度量值是大的好，还是小的好
res8: Boolean = false // 这里显示“评估的度量值”是小的好
cvModel.getNumFolds // 交叉验证的折数
res9: Int = 3
//################################
// 测试模型
val predictDF: DataFrame = cvModel.transform(testDF).selectExpr(
| //"race","poverty","smoke","alcohol","agemth","ybirth","yschool","pc3mth", "features",
| "label", "censor",
| "round(prediction,2) as prediction").orderBy("label")
predictDF: org.apache.spark.sql.DataFrame = [label: double, censor: double ... 1 more field]
predictDF.show
+-----+------+----------+
|label|censor|prediction|
+-----+------+----------+
| 1.0| 1.0| 15.4|
| 1.0| 1.0| 20.02|
| 1.0| 1.0| 18.73|
| 1.0| 1.0| 21.58|
| 1.0| 1.0| 21.8|
| 1.0| 1.0| 21.8|
| 1.0| 1.0| 14.37|
| 1.0| 1.0| 13.5|
| 1.0| 1.0| 15.82|
| 1.0| 1.0| 19.51|
| 1.0| 1.0| 13.17|
| 1.0| 1.0| 11.9|
| 1.0| 1.0| 17.26|
| 1.0| 1.0| 13.57|
| 1.0| 1.0| 11.57|
| 1.0| 1.0| 13.55|
| 1.0| 1.0| 10.95|
| 1.0| 1.0| 14.92|
| 1.0| 1.0| 12.25|
| 1.0| 1.0| 19.62|
+-----+------+----------+
only showing top 20 rows