Running ‘testthat.R’ [18s/30s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(regfilter)
  > 
  > test_check("regfilter")
  [ FAIL 88 | WARN 0 | SKIP 0 | PASS 94 ]
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-regAENN.R:8:3'): the result has the correct class ──────────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:8:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:24:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:40:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:56:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:82:3'): y is a double vector ─────────────────────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:82:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:100:3'): the result has the correct sum.rfdata ───────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:100:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:118:3'): the result shown the print of summary ───────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:118:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regAENN.R:136:3'): the result shown the print of summary ───────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regAENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regAENN.R:136:2
   2. └─regfilter:::regAENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regBBNR.R:8:3'): the result has the correct class ──────────────
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:8:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:24:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:40:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:56:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:82:3'): y is a double vector ─────────────────────────
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:82:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:100:3'): the result has the correct sum.rfdata ───────
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:100:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:118:3'): the result shown the print of summary ───────
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:118:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regBBNR.R:136:3'): the result shown the print of summary ───────
  Error in `get.knn(data = dataset[, -output], k = k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regBBNR(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regBBNR.R:136:2
   2. └─regfilter:::regBBNR.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k, algorithm = "brute")
  ── Error ('test-regCNN.R:8:3'): the result has the correct class ───────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:8:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:23:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:23:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:39:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:39:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:55:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:55:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:81:3'): y is a double vector ──────────────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:81:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:99:3'): the result has the correct sum.rfdata ─────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:99:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:117:3'): the result shown the print of summary ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:117:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regCNN.R:135:3'): the result shown the print of summary ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regCNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regCNN.R:135:2
   2. └─regfilter:::regCNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:8:3'): the result has the correct class ────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:8:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:24:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:40:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:56:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:82:3'): y is a double vector ───────────────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:82:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:100:3'): the result has the correct sum.rfdata ─────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:100:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:118:3'): the result shown the print of summary ─────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:118:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regDF.R:136:3'): the result shown the print of summary ─────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─regfilter::regDF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regDF.R:136:2
    2. └─regfilter:::regDF.default(...)
    3.   └─base::sapply(...)
    4.     └─base::lapply(X = X, FUN = FUN, ...)
    5.       └─regfilter (local) FUN(X[[i]], ...)
    6.         └─regfilter:::pred_met(key, dataset, dataset, output, t)
    7.           └─base::sapply(...)
    8.             └─base::lapply(X = X, FUN = FUN, ...)
    9.               └─regfilter (local) FUN(X[[i]], ...)
   10.                 └─FNN::knn.reg(...)
   11.                   └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:8:3'): the result has the correct class ────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:8:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:23:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:23:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:39:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:39:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:55:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:55:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:81:3'): y is a double vector ───────────────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:81:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:99:3'): the result has the correct sum.rfdata ──────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:99:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:117:3'): the result shown the print of summary ─────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:117:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regEF.R:135:3'): the result shown the print of summary ─────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regEF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regEF.R:135:2
   2. └─regfilter:::regEF.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regENN.R:8:3'): the result has the correct class ───────────────
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:8:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:24:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:40:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:56:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:82:3'): y is a double vector ──────────────────────────
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:82:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:100:3'): the result has the correct sum.rfdata ────────
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:100:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:118:3'): the result shown the print of summary ────────
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:118:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regENN.R:136:3'): the result shown the print of summary ────────
  Error in `get.knn(data = dataset[, -output], k, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regENN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regENN.R:136:2
   2. └─regfilter:::regENN.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k, algorithm = "brute")
  ── Error ('test-regFMF.R:8:3'): the result has the correct class ───────────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:8:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:24:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:40:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:56:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:82:3'): y is a double vector ──────────────────────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:82:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:100:3'): the result has the correct sum.rfdata ────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:100:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:118:3'): the result shown the print of summary ────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:118:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regFMF.R:136:3'): the result shown the print of summary ────────
  Error in `get.knn(data = dataset[, -output], k = j, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regFMF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regFMF.R:136:2
   2. └─regfilter:::regFMF.default(...)
   3.   ├─regfilter::regAENN(x = x, y = y, t = t)
   4.   └─regfilter:::regAENN.default(x = x, y = y, t = t)
   5.     └─FNN::get.knn(data = dataset[, -output], k = j, algorithm = "brute")
  ── Error ('test-regGE.R:8:3'): the result has the correct class ────────────────
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:8:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:24:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:40:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:56:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:82:3'): y is a double vector ───────────────────────────
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:82:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:100:3'): the result has the correct sum.rfdata ─────────
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:100:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:118:3'): the result shown the print of summary ─────────
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:118:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regGE.R:136:3'): the result shown the print of summary ─────────
  Error in `get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regGE(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regGE.R:136:2
   2. └─regfilter:::regGE.default(...)
   3.   └─FNN::get.knn(data = dataset[, -output], k = k - 1, algorithm = "brute")
  ── Error ('test-regHRRF.R:8:3'): the result has the correct class ──────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:8:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:24:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:40:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:56:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:82:3'): y is a double vector ─────────────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:82:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:100:3'): the result has the correct sum.rfdata ───────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:100:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:118:3'): the result shown the print of summary ───────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:118:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regHRRF.R:136:3'): the result shown the print of summary ───────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regHRRF(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regHRRF.R:136:2
   2. └─regfilter:::regHRRF.default(...)
   3.   └─regfilter:::predictions(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:8:3'): the result has the correct class ───────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:8:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:24:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:40:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:56:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:82:3'): y is a double vector ──────────────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:82:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:100:3'): the result has the correct sum.rfdata ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:100:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:118:3'): the result shown the print of summary ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:118:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRND.R:136:3'): the result shown the print of summary ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRND(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRND.R:136:2
   2. └─regfilter:::regRND.default(...)
   3.   └─regfilter:::testing(...)
   4.     └─FNN::knn.reg(...)
   5.       └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:8:3'): the result has the correct class ───────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:8:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:24:3'): the number of idclean plus idnoise equals the number of dataset samples ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:24:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:40:3'): the idclean and idnoise are equal to dataset rownames ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:40:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:56:3'): the original dataset can be correctly reconstructed from the rfdata object ──
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:56:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:82:3'): y is a double vector ──────────────────────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:82:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:100:3'): the result has the correct sum.rfdata ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:100:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:118:3'): the result shown the print of summary ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:118:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  ── Error ('test-regRNN.R:136:3'): the result shown the print of summary ────────
  Error in `get.knnx(train, test, k, algorithm)`: DLL requires the use of native symbols
  Backtrace:
      ▆
   1. ├─regfilter::regRNN(x = rock[, -ncol(rock)], y = rock[, ncol(rock)]) at test-regRNN.R:136:2
   2. └─regfilter:::regRNN.default(...)
   3.   └─FNN::knn.reg(...)
   4.     └─FNN::get.knnx(train, test, k, algorithm)
  
  [ FAIL 88 | WARN 0 | SKIP 0 | PASS 94 ]
  Error: Test failures
  Execution halted