Сервер h2o дает сбой, когда я запускаю поиск по сетке

Я делаю поиск по сетке по модели классификации. Когда сервер h20 запускается, я получаю:

R is connected to the H2O cluster: 
    H2O cluster uptime:         9 minutes 35 seconds 
    H2O cluster version:        3.10.4.8 
    H2O cluster version age:    14 days, 4 hours and 1 minute  
    H2O cluster name:           H2O_started_from_R_Charles_huu844 
    H2O cluster total nodes:    1 
    H2O cluster total memory:   21.31 GB 
    H2O cluster total cores:    8 
    H2O cluster allowed cores:  8 
    H2O cluster healthy:        TRUE 
    H2O Connection ip:          localhost 
    H2O Connection port:        54321 
    H2O Connection proxy:       NA 
    H2O Internal Security:      FALSE 
    R Version:                  R version 3.2.2 (2015-08-14) 

Когда моя модель входит в поиск по сетке, я получаю следующее сообщение об ошибке:

ERROR: Unexpected HTTP Status code: 412 Precondition Failed (url = http://localhost:54321/99/Grids/mygrid?sort_by=auc&decreasing=TRUE)

water.exceptions.H2OIllegalArgumentException
 [1] "water.exceptions.H2OIllegalArgumentException: Invalid argument for sort_by specified. Must be one of: [r2, mean_per_class_accuracy, max_per_class_error, err, total_rows, rmse, accuracy, err_count, logloss, mse, mean_per_class_error]"
 [2] "    hex.schemas.GridSchemaV99.fillFromImpl(GridSchemaV99.java:114)" 

Мой R-скрипт выглядит следующим образом:

rm(list=ls())
options(scipen=999) # remove E notation
ptm <- proc.time()

if (Sys.info()["sysname"] == "Windows") {
  filePath = "//bigsur/sm/Trending/model.csv"
  homedir = "c:/sm/Trending/"
  setwd("c:/sm/Trending/R")
  sink("C:/Users/Charles/Desktop/log.txt")
} else {
  filePath = "/Volumes/sm/Trending/model.csv"
  homedir = "/Volumes/sm/Trending/"
  setwd("/Volumes/sm/Trending/R")
  sink("~/Desktop/log.txt")
}

#install.packages("ggplot2")
#install.packages("dplyr")

sink.reset <- function(){
  for(i in seq_len(sink.number())){
    sink(NULL)
  }
}

printf <- function(...) print(sprintf(...))

results = function(title, best_model) {
  best_params = best_model@parameters
  best_activation            <<- best_model@parameters$activation
  best_hidden                <<- best_model@parameters$hidden
  best_l1                    <<- best_model@parameters$l1
  best_l2                    <<- best_model@parameters$l2
  best_input_dropout_ratio   <<- best_model@parameters$input_dropout_ratio
  best_hidden_dropout_ratios <<- best_model@parameters$hidden_dropout_ratios

  printf(" ")
  printf("%s", title)
  best_model
  plot(best_model)
  h2o.performance(best_model)
  h2o.performance(best_model, valid = TRUE)
  h2o.mse(best_model, valid = TRUE)

  printf("mse: %f", best_model@model$validation_metrics@metrics$MSE)
  printf("best activation: %s", best_activation)
  cat("best hidden layers: ", best_hidden, "\n")
  printf("Best l1: %f", best_l1)
  printf("Best l2: %f", best_l2)
  #printf("best_input_dropout_ratio: %f", best_input_dropout_ratio)
  #cat("Best best_hidden_dropout_ratios: ", best_hidden_dropout_ratios, "\n")

  predictions = h2o.predict(best_model, test)
  summary(predictions, exact_quantiles=TRUE)
  predicted = predictions[,1]
  test_targets = test[, 5]
  correct = predicted == test_targets
  numCorrect = as.integer(sum(correct))
  ntotal = as.integer(nrow(correct))
  percent = round(numCorrect/ntotal*100, 2)
  printf("Correct classifications on all data: %d/%d (%f)", numCorrect, ntotal, percent)

  #predicted.h2o = h2o.assign(predicted, key = "predicted.h2o")
  #correct.h2o = h2o.assign(correct, key = "correct.h2o")

  perf_test = h2o.performance(model = best_model, newdata = test)
  cat("\nPerformance on test dataset\n")
  print(perf_test)
  cat("\nConfusion matrix on test dataset\n")
  h2o.confusionMatrix(perf_test)

  # Plot Receiver Operating Characteristic (ROC) curve and find its Area Under the Curve (AUC)
  # A ROC curve is a graph of the true positive rate (recall) against the false positive
  # rate for a binary classifier.
  #plot(f1_best_model, type = "cutoffs", col = "blue")

  cm = h2o.confusionMatrix(best_model, train)
  print("Confusion Matrix: ")
  print(cm)
  true_negative = cm[1,1]
  true_positive = cm[2,2]
  false_negative = cm[2,1]
  false_positive = cm[1,2]
  total = true_negative + true_positive + false_negative + false_positive
  accuracy = (true_positive + true_negative)/total
  printf("accuracy: %f", accuracy)

  misclassification_rate = (false_positive + false_negative)/total
  printf("misclassification_rate: %f", misclassification_rate)

  cat("\nVariable importance\n")
  print(best_model@model$variable_importance)

  return_list = c(best_activation,
                  best_hidden,
                  best_l1,
                  best_l2,
                  best_input_dropout_ratio,
                  best_hidden_dropout_ratios)

  return (return_list)
}

library(h2o)
library(dplyr)
library(data.table)
library(ggplot2)

localH2O = h2o.init(ip = "localhost",
                    port = 54321,
                    startH2O = TRUE,
                    max_mem_size="24G",
                    nthreads = -1)
h2o.no_progress()
h2o.removeAll() ## clean slate - just in case the cluster was already running


print(filePath)
model.full <- read.csv(filePath, header = TRUE, sep = ",")
head(model.full)
remove = !colnames(model.full) %in% c("Date",
                                      "Symbol",
                                      "BuyIndex",
                                      "SellIndex",
                                      "BoxRatio",
                                      "Acceleration",
                                      "nPosVelo",
                                      "Gain")
model_orig = model.full[, remove]
head(model_orig)
model = model_orig[sample(nrow(model_orig)),] # shuffle the rows
head(model)

df <- as.h2o(model, destination_frame = "df")

splits <- h2o.splitFrame(df, c(0.6,0.2), seed=1234)
train  <- h2o.assign(splits[[1]], "train.hex") # 60%
valid  <- h2o.assign(splits[[2]], "valid.hex") # 20%
test   <- h2o.assign(splits[[3]], "test.hex")  # 20%

printf("train----------------------------------------")
head(train)
train
printf("valid----------------------------------------")
#head(valid)
valid
printf("test-----------------------------------------")
#head(test)
test

p1 = train$Thrust
p2 = train$Velocity
p3 = train$OnBalRun
p4 = train$vwapGain
p1d = rbind(lapply(p1, as.double))  # p1 is an environment variable, we need doubles
p2d = rbind(lapply(p2, as.double))
p3d = rbind(lapply(p3, as.double))
p4d = rbind(lapply(p4, as.double))
a = unlist(p1d)
b = unlist(p2d)
c = unlist(p3d)
d = unlist(p4d)

pairs(train[1:4], main = "Scatterplot of predictors", pch = 21, cex = 0.8, bg = c("green3", "red")[unclass(model$Altitude)])

cat("\n\n1. Summary of train dataset------------------------------------------------------\n")
summary(train, exact_quantiles=TRUE)

cat("\n\n2. Grid Search on valid data ----------------------------------------------------\n")

activation_opts = c("RectifierWithDropout","TanhWithDropout","MaxoutWithDropout")
hidden_opts = list(c(80),c(100),c(200),c(300),c(400),c(500),
                   c(80,80),c(100,100),c(200,200),c(300,300),c(400,400),c(500,500),
                   c(80,80,80,80),c(100,100,100,100),c(200,200,200,200),c(300,300,300,300),
                   c(80,80,80,80,80),c(100,100,100,100,100),c(200,200,200,200,200),
                   c(300,300,300,300,300),c(400,400,400,400,400),c(500,500,500,500,500),
                   c(80,80,80,80,80,80),c(100,100,100,100,100,100),c(200,200,200,200,200,200),
                   c(300,300,300,300,300,300),c(400,400,400,400,400,400),
                   c(500,500,500,500,500,500)
                   )
l1_opts = runif(1, 0, 0.0001)
l2_opts = runif(1, 0, 0.0001)

hyperparams = list(
  activation = activation_opts,
  hidden = hidden_opts,
  l1 = l1_opts,
  l2 = l2_opts,
  max_w2 = 10
)

search_criteria = list(strategy = "RandomDiscrete",
                       stopping_metric = "misclassification",
                       max_models = 10000,
                       max_runtime_secs = 72000,
                       stopping_tolerance = 0.00001,
                       stopping_rounds = 10)

grid_model = h2o.grid(algorithm = "deeplearning",
                      grid_id = "mygrid",
                      hyper_params = hyperparams,
                      search_criteria = search_criteria,
                      x = 1:4,
                      y = 5,
                      training_frame = train,
                      validation_frame = valid,
                      variable_importances = TRUE,
                      balance_classes=TRUE,
                      score_training_samples=1000,
                      score_validation_samples=1000,
                      score_validation_sampling="Stratified",
                      epochs = 1000000,
                      seed = 7)

cat("\n\n3. Summary of grid_model---------------------------------------------------------\n")
grid = h2o.getGrid("mygrid", sort_by="auc", decreasing=TRUE)
summary(grid)

cat("\n\n4. Performance of best_model-----------------------------------------------------\n")
best_model = h2o.getModel(grid@model_ids[[1]])

results("5.best_model", best_model)

cat("\n\n6. Performance valid dataset-----------------------------------------------------\n")
perf_valid = h2o.performance(model = best_model, newdata = valid)
perf_valid

cat("\n\n7. Performance on test dataset---------------------------------------------------\n")
perf_test = h2o.performance(model = best_model, newdata = test)
perf_test

plot(perf_test, type="roc")     # Plot the roc curve

predicted <- h2o.predict( best_model, test )
actual = test[,5]
cat("\n\n8. Mean prediction on the test set: ", 100*mean( predicted$predict == actual ), "%\n")
correct = predicted == actual
numCorrect = as.integer(sum(correct))
ntotal = as.integer(nrow(correct))
percent = round(numCorrect/ntotal*100, 2)
printf("9. Test of Mean prediction on the test set: %d/%d (%f)", numCorrect, ntotal, percent)
cat("\n\n10. The 'test' set auc is: ", h2o.auc(perf_test), "\n")

p = h2o.saveModel(best_model, path = "C:\\sm\\Trending\\h2o_model", force = TRUE)
p

minutes = (proc.time() - ptm)[1]
printf("Elapsed time: %.2f minutes", minutes)

unlink("log.txt")
sink.reset()

Мой журнал:

 Connection successful!

R is connected to the H2O cluster: 
    H2O cluster uptime:         9 minutes 35 seconds 
    H2O cluster version:        3.10.4.8 
    H2O cluster version age:    14 days, 4 hours and 1 minute  
    H2O cluster name:           H2O_started_from_R_Charles_huu844 
    H2O cluster total nodes:    1 
    H2O cluster total memory:   21.31 GB 
    H2O cluster total cores:    8 
    H2O cluster allowed cores:  8 
    H2O cluster healthy:        TRUE 
    H2O Connection ip:          localhost 
    H2O Connection port:        54321 
    H2O Connection proxy:       NA 
    H2O Internal Security:      FALSE 
    R Version:                  R version 3.2.2 (2015-08-14) 

[1] 0
[1] "//bigsur/sm/Trending/model.csv"
        Date Symbol BuyIndex SellIndex BoxRatio  Thrust Acceleration Velocity nPosVelo
1   4/5/2017 GBX         132       199   77.724 49.7190     107.5811   2.9236       59
2   1/5/2017 RH          216       259    4.838  4.8380     137.0574   0.3381       14
3  9/28/2016 DDS         149       444    0.150  0.4860      99.1360   0.1081       59
4 11/25/2016 JKS         132       186    0.932  0.8686      38.9931   0.6057       59
5 12/12/2016 JNUG        132       177    0.582  0.3242      87.1144   1.1274       18
6   3/7/2017 LPL         134       180    8.954  8.9540      34.1691   0.4778       59
  OnBalRun vwapGain    Gain Altitude
1  12.6378  90.0656 -0.1659       no
2   1.5157   0.9495 -0.6496       no
3   0.5476   2.2887  4.1439      yes
4   3.2719   3.8235  0.5051       no
5   2.5006  12.0472 -0.8942       no
6   2.9935   1.1234 -0.1617       no
   Thrust Velocity OnBalRun vwapGain Altitude
1 49.7190   2.9236  12.6378  90.0656       no
2  4.8380   0.3381   1.5157   0.9495       no
3  0.4860   0.1081   0.5476   2.2887      yes
4  0.8686   0.6057   3.2719   3.8235       no
5  0.3242   1.1274   2.5006  12.0472       no
6  8.9540   0.4778   2.9935   1.1234       no
     Thrust Velocity OnBalRun vwapGain Altitude
4427 0.9370   0.3176   1.2786   2.3151       no
3079 2.2060   0.9261   1.1257   1.2506       no
3952 0.0702   0.4430   1.1485   0.9928       no
7765 1.1596   1.1067   6.2563   2.1164      yes
1682 0.6708   0.4519   1.3848   2.1808       no
5145 4.5600   0.3462   1.7386   0.7722       no
[1] "train----------------------------------------"
  Thrust Velocity OnBalRun vwapGain Altitude
1 2.2060   0.9261   1.1257   1.2506       no
2 0.6708   0.4519   1.3848   2.1808       no
3 4.5600   0.3462   1.7386   0.7722       no
4 3.6930   3.2778  11.4092  49.3335       no
5 0.9980   0.4035   1.6667   1.1264       no
6 0.2016   0.5627   2.4101   1.2642       no
  Thrust Velocity OnBalRun vwapGain Altitude
1 2.2060   0.9261   1.1257   1.2506       no
2 0.6708   0.4519   1.3848   2.1808       no
3 4.5600   0.3462   1.7386   0.7722       no
4 3.6930   3.2778  11.4092  49.3335       no
5 0.9980   0.4035   1.6667   1.1264       no
6 0.2016   0.5627   2.4101   1.2642       no

[5548 rows x 5 columns] 
[1] "valid----------------------------------------"
  Thrust Velocity OnBalRun vwapGain Altitude
1 0.9370   0.3176   1.2786   2.3151       no
2 0.0702   0.4430   1.1485   0.9928       no
3 1.0230   0.3119   3.0922   0.8788       no
4 6.4100   0.9966   5.3490   2.9436      yes
5 6.9620   0.7004   3.5810   4.8905       no
6 1.6800   1.4518   5.1933   1.7955       no

[1875 rows x 5 columns] 
[1] "test-----------------------------------------"
  Thrust Velocity OnBalRun vwapGain Altitude
1 1.1596   1.1067   6.2563   2.1164      yes
2 4.7010   0.5369   1.1266   7.5566       no
3 1.7110   0.9247   3.5819   3.0598       no
4 1.4620   0.3315   4.3097   0.4129       no
5 0.5610   0.4494   1.8738   1.3942       no
6 6.7255   1.7309   5.6268   4.4937      yes

[1823 rows x 5 columns] 


1. Summary of train dataset------------------------------------------------------
 Thrust               Velocity          OnBalRun           vwapGain           Altitude  
 Min.   :   -1.4845   Min.   :-0.1241   Min.   : -0.5299   Min.   : -4.7648    no :4875 
 1st Qu.:    0.3984   1st Qu.: 0.3281   1st Qu.:  1.1468   1st Qu.:  0.8684    yes: 671 
 Median :    1.0425   Median : 0.3815   Median :  1.6439   Median :  1.9954       :   2 
 Mean   :   12.1332   Mean   : 0.5913   Mean   :  2.5911   Mean   :  4.8876             
 3rd Qu.:    1.9723   3rd Qu.: 0.5716   3rd Qu.:  2.6507   3rd Qu.:  4.7500             
 Max.   :41279.8960   Max.   :29.4449   Max.   :154.5988   Max.   :314.7143             
 NA's   :2            NA's   :2         NA's   :2          NA's   :2                    


2. Grid Search on valid data ----------------------------------------------------


3. Summary of grid_model---------------------------------------------------------

ERROR: Unexpected HTTP Status code: 412 Precondition Failed (url = http://localhost:54321/99/Grids/mygrid?sort_by=auc&decreasing=TRUE)

water.exceptions.H2OIllegalArgumentException
 [1] "water.exceptions.H2OIllegalArgumentException: Invalid argument for sort_by specified. Must be one of: [r2, mean_per_class_accuracy, max_per_class_error, err, total_rows, rmse, accuracy, err_count, logloss, mse, mean_per_class_error]"
 [2] "    hex.schemas.GridSchemaV99.fillFromImpl(GridSchemaV99.java:114)"                                                                                                                                                                      
 [3] "    water.api.GridsHandler.fetch(GridsHandler.java:41)"                                                                                                                                                                                  
 [4] "    sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)"                                                                                                                                                                         
 [5] "    sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)"                                                                                                                                                       
 [6] "    sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)"                                                                                                                                               
 [7] "    java.lang.reflect.Method.invoke(Method.java:498)"                                                                                                                                                                                    
 [8] "    water.api.Handler.handle(Handler.java:61)"                                                                                                                                                                                           
 [9] "    water.api.RequestServer.serve(RequestServer.java:436)"                                                                                                                                                                               
[10] "    water.api.RequestServer.doGeneric(RequestServer.java:285)"                                                                                                                                                                           
[11] "    water.api.RequestServer.doGet(RequestServer.java:220)"                                                                                                                                                                               
[12] "    javax.servlet.http.HttpServlet.service(HttpServlet.java:735)"                                                                                                                                                                        
[13] "    javax.servlet.http.HttpServlet.service(HttpServlet.java:848)"                                                                                                                                                                        
[14] "    org.eclipse.jetty.servlet.ServletHolder.handle(ServletHolder.java:684)"                                                                                                                                                              
[15] "    org.eclipse.jetty.servlet.ServletHandler.doHandle(ServletHandler.java:503)"                                                                                                                                                          
[16] "    org.eclipse.jetty.server.handler.ContextHandler.doHandle(ContextHandler.java:1086)"                                                                                                                                                  
[17] "    org.eclipse.jetty.servlet.ServletHandler.doScope(ServletHandler.java:429)"                                                                                                                                                           
[18] "    org.eclipse.jetty.server.handler.ContextHandler.doScope(ContextHandler.java:1020)"                                                                                                                                                   
[19] "    org.eclipse.jetty.server.handler.ScopedHandler.handle(ScopedHandler.java:135)"                                                                                                                                                       
[20] "    org.eclipse.jetty.server.handler.HandlerCollection.handle(HandlerCollection.java:154)"                                                                                                                                               
[21] "    org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:116)"                                                                                                                                                     
[22] "    water.JettyHTTPD$LoginHandler.handle(JettyHTTPD.java:417)"                                                                                                                                                                           
[23] "    org.eclipse.jetty.server.handler.HandlerCollection.handle(HandlerCollection.java:154)"                                                                                                                                               
[24] "    org.eclipse.jetty.server.handler.HandlerWrapper.handle(HandlerWrapper.java:116)"                                                                                                                                                     
[25] "    org.eclipse.jetty.server.Server.handle(Server.java:370)"                                                                                                                                                                             
[26] "    org.eclipse.jetty.server.AbstractHttpConnection.handleRequest(AbstractHttpConnection.java:494)"                                                                                                                                      
[27] "    org.eclipse.jetty.server.BlockingHttpConnection.handleRequest(BlockingHttpConnection.java:53)"                                                                                                                                       
[28] "    org.eclipse.jetty.server.AbstractHttpConnection.headerComplete(AbstractHttpConnection.java:971)"                                                                                                                                     
[29] "    org.eclipse.jetty.server.AbstractHttpConnection$RequestHandler.headerComplete(AbstractHttpConnection.java:1033)"                                                                                                                     
[30] "    org.eclipse.jetty.http.HttpParser.parseNext(HttpParser.java:644)"                                                                                                                                                                    
[31] "    org.eclipse.jetty.http.HttpParser.parseAvailable(HttpParser.java:235)"                                                                                                                                                               
[32] "    org.eclipse.jetty.server.BlockingHttpConnection.handle(BlockingHttpConnection.java:72)"                                                                                                                                              
[33] "    org.eclipse.jetty.server.bio.SocketConnector$ConnectorEndPoint.run(SocketConnector.java:264)"                                                                                                                                        
[34] "    org.eclipse.jetty.util.thread.QueuedThreadPool.runJob(QueuedThreadPool.java:608)"                                                                                                                                                    
[35] "    org.eclipse.jetty.util.thread.QueuedThreadPool$3.run(QueuedThreadPool.java:543)"                                                                                                                                                     
[36] "    java.lang.Thread.run(Thread.java:745)"                                                                                                                                                                                               



4. Performance of best_model-----------------------------------------------------


6. Performance valid dataset-----------------------------------------------------


7. Performance on test dataset---------------------------------------------------
Called from: sprintf(...)
[1] "Elapsed time: 85.98 minutes"

Пожалуйста помоги.

Чарльз