Last updated on 2025-12-06 00:49:02 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.1-0 | 3.36 | 88.16 | 91.52 | OK | |
| r-devel-linux-x86_64-debian-gcc | 2.1-0 | 2.35 | 31.72 | 34.07 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 2.1-0 | 133.94 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 2.1-0 | 144.88 | OK | |||
| r-devel-windows-x86_64 | 2.1-0 | 6.00 | 126.00 | 132.00 | OK | |
| r-patched-linux-x86_64 | 2.1-0 | 3.61 | 76.76 | 80.37 | OK | |
| r-release-linux-x86_64 | 2.1-0 | 3.25 | 81.87 | 85.12 | OK | |
| r-release-macos-arm64 | 2.1-0 | OK | ||||
| r-release-macos-x86_64 | 2.1-0 | 3.00 | 93.00 | 96.00 | OK | |
| r-release-windows-x86_64 | 2.1-0 | 6.00 | 126.00 | 132.00 | OK | |
| r-oldrel-macos-arm64 | 2.1-0 | OK | ||||
| r-oldrel-macos-x86_64 | 2.1-0 | 2.00 | 75.00 | 77.00 | OK | |
| r-oldrel-windows-x86_64 | 2.1-0 | 4.00 | 149.00 | 153.00 | OK |
Version: 2.1-0
Check: examples
Result: ERROR
Running examples in ‘ssc-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: coBC
> ### Title: CoBC method
> ### Aliases: coBC
>
> ### ** Examples
>
>
> library(ssc)
>
> ## Load Wine data set
> data(wine)
>
> cls <- which(colnames(wine) == "Wine")
> x <- wine[, -cls] # instances without classes
> y <- wine[, cls] # the classes
> x <- scale(x) # scale the attributes
>
> ## Prepare data
> set.seed(20)
> # Use 50% of instances for training
> tra.idx <- sample(x = length(y), size = ceiling(length(y) * 0.5))
> xtrain <- x[tra.idx,] # training instances
> ytrain <- y[tra.idx] # classes of training instances
> # Use 70% of train instances as unlabeled set
> tra.na.idx <- sample(x = length(tra.idx), size = ceiling(length(tra.idx) * 0.7))
> ytrain[tra.na.idx] <- NA # remove class information of unlabeled instances
>
> # Use the other 50% of instances for inductive testing
> tst.idx <- setdiff(1:length(y), tra.idx)
> xitest <- x[tst.idx,] # testing instances
> yitest <- y[tst.idx] # classes of testing instances
>
> ## Example: Training from a set of instances with 1-NN as base classifier.
> set.seed(1)
> m1 <- coBC(x = xtrain, y = ytrain,
+ learner = caret::knn3,
+ learner.pars = list(k = 1),
+ pred = "predict")
Error in loadNamespace(x) : there is no package called ‘caret’
Calls: coBC ... loadNamespace -> withRestarts -> withOneRestart -> doWithOneRestart
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 2.1-0
Check: tests
Result: ERROR
Running ‘testthat.R’ [5s/5s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(ssc)
>
> test_check("ssc")
Saving _problems/test_Democratic-10.R
Saving _problems/test_Democratic-58.R
Saving _problems/test_Democratic-66.R
Saving _problems/test_Democratic-77.R
Saving _problems/test_Democratic-93.R
Saving _problems/test_Democratic-104.R
Saving _problems/test_Democratic-115.R
Saving _problems/test_Democratic-169.R
Saving _problems/test_SETRED-9.R
Saving _problems/test_SETRED-28.R
Saving _problems/test_SETRED-38.R
Saving _problems/test_SETRED-52.R
Saving _problems/test_SETRED-62.R
Saving _problems/test_SETRED-72.R
Saving _problems/test_SETRED-122.R
Saving _problems/test_SETRED-138.R
Saving _problems/test_SETRED-154.R
Saving _problems/test_SETRED-170.R
Saving _problems/test_SelfTraining-9.R
Saving _problems/test_SelfTraining-29.R
Saving _problems/test_SelfTraining-39.R
Saving _problems/test_SelfTraining-52.R
Saving _problems/test_SelfTraining-61.R
Saving _problems/test_SelfTraining-71.R
Saving _problems/test_SelfTraining-117.R
Saving _problems/test_SelfTraining-133.R
Saving _problems/test_SelfTraining-149.R
Saving _problems/test_SelfTraining-165.R
Saving _problems/test_TriTraining-9.R
Saving _problems/test_TriTraining-28.R
Saving _problems/test_TriTraining-38.R
Saving _problems/test_TriTraining-53.R
Saving _problems/test_TriTraining-63.R
Saving _problems/test_TriTraining-73.R
Saving _problems/test_TriTraining-123.R
Saving _problems/test_coBC-9.R
Saving _problems/test_coBC-28.R
Saving _problems/test_coBC-38.R
Saving _problems/test_coBC-53.R
Saving _problems/test_coBC-63.R
Saving _problems/test_coBC-73.R
Saving _problems/test_coBC-123.R
Saving _problems/test_coBC-139.R
Saving _problems/test_coBC-155.R
Saving _problems/test_coBC-172.R
Saving _problems/test_coBC-188.R
[ FAIL 46 | WARN 5 | SKIP 3 | PASS 89 ]
══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• {caret} is not installed. (3): 'test_DemocraticG.R:5:1',
'test_TriTrainingG.R:4:1', 'test_coBCG.R:4:1'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_Democratic.R:9:5'): democratic works ───────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::democratic(...) at test_Democratic.R:9:5
2. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:56:5'): the learners information is complete ──────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_Democratic.R:56:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::democratic(...)
5. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:65:5'): prediction not fail when x is a vector ────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::democratic(...) at test_Democratic.R:65:5
2. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:76:5'): the model structure is correct ────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::democratic(...) at test_Democratic.R:76:5
2. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:89:5'): x can be a data.frame ─────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_Democratic.R:89:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::democratic(...)
5. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:100:5'): y can be a vector ────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_Democratic.R:100:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::democratic(...)
5. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:111:5'): x.inst can be coerced to logical ─────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_Democratic.R:111:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::democratic(...)
5. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_Democratic.R:165:5'): x is a square matrix when x.inst is FALSE ──
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_Democratic.R:165:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::democratic(...)
5. └─ssc:::as.list2(learners.pars, length(learners))
── Error ('test_SETRED.R:9:5'): setred works ───────────────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::setred(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_SETRED.R:9:5
2. └─ssc::setredG(...)
3. └─ssc (local) gen.learner(labeled, ynew[labeled])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:28:5'): prediction not fail when x is a vector ────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::setred(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_SETRED.R:28:5
2. └─ssc::setredG(...)
3. └─ssc (local) gen.learner(labeled, ynew[labeled])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:38:5'): the model structure is correct ────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::setred(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_SETRED.R:38:5
2. └─ssc::setredG(...)
3. └─ssc (local) gen.learner(labeled, ynew[labeled])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:49:5'): x can be a data.frame ─────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:49:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(...)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:59:5'): y can be a vector ─────────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:59:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(x = wine$xtrain, y = as.vector(wine$ytrain), learner = knn3)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:69:5'): x.inst can be coerced to logical ──────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:69:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(...)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:119:5'): x is a square matrix when x.inst is FALSE ────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:119:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(...)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(...)
8. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:135:5'): max.iter is a value greather than 0 ──────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:135:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(...)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:151:5'): perc.full is a value between 0 and 1 ─────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:151:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(...)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SETRED.R:167:5'): theta is a value between 0 and 1 ─────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SETRED.R:167:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::setred(...)
5. └─ssc::setredG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:9:5'): selfTraining works ───────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::selfTraining(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_SelfTraining.R:9:5
2. └─ssc::selfTrainingG(...)
3. └─ssc (local) gen.learner(labeled, ynew[labeled])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:29:5'): prediction not fail when x is a vector ──
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::selfTraining(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_SelfTraining.R:29:5
2. └─ssc::selfTrainingG(...)
3. └─ssc (local) gen.learner(labeled, ynew[labeled])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:39:5'): the model structure is correct ──────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::selfTraining(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_SelfTraining.R:39:5
2. └─ssc::selfTrainingG(...)
3. └─ssc (local) gen.learner(labeled, ynew[labeled])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:51:5'): x can be a data.frame ───────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:51:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(x, y = wine$ytrain, learner = knn3)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:60:5'): y can be a vector ───────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:60:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(x = wine$xtrain, y, learner = knn3)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:68:5'): x.inst can be coerced to logical ────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:68:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(...)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:114:5'): x is a square matrix when x.inst is FALSE ──
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:114:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(...)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(...)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:130:5'): max.iter is a value greather than 0 ────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:130:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(...)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:146:5'): perc.full is a value between 0 and 1 ───
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:146:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(...)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_SelfTraining.R:162:5'): thr.conf is a value between 0 and 1 ────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_SelfTraining.R:162:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::selfTraining(...)
5. └─ssc::selfTrainingG(...)
6. └─ssc (local) gen.learner(labeled, ynew[labeled])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:9:5'): triTraining works ─────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::triTraining(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_TriTraining.R:9:5
2. └─ssc::triTrainingG(y, gen.learner2, gen.pred2)
3. └─ssc (local) gen.learner(indexes, y[indexes])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:28:5'): prediction not fail when x is a vector ───
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::triTraining(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_TriTraining.R:28:5
2. └─ssc::triTrainingG(y, gen.learner2, gen.pred2)
3. └─ssc (local) gen.learner(indexes, y[indexes])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:38:5'): the model structure is correct ───────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::triTraining(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_TriTraining.R:38:5
2. └─ssc::triTrainingG(y, gen.learner2, gen.pred2)
3. └─ssc (local) gen.learner(indexes, y[indexes])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:50:5'): x can be a data.frame ────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_TriTraining.R:50:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::triTraining(...)
5. └─ssc::triTrainingG(y, gen.learner2, gen.pred2)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:60:5'): y can be a vector ────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_TriTraining.R:60:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::triTraining(...)
5. └─ssc::triTrainingG(y, gen.learner2, gen.pred2)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:70:5'): x.inst can be coerced to logical ─────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_TriTraining.R:70:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::triTraining(...)
5. └─ssc::triTrainingG(y, gen.learner2, gen.pred2)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_TriTraining.R:120:5'): x is a square matrix when x.inst is FALSE ──
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_TriTraining.R:120:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::triTraining(...)
5. └─ssc::triTrainingG(y, gen.learner1, gen.pred1)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(...)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:9:5'): coBC works ───────────────────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_coBC.R:9:5
2. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
3. └─ssc (local) gen.learner(indexes, y[indexes])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:28:5'): prediction not fail when x is a vector ──────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_coBC.R:28:5
2. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
3. └─ssc (local) gen.learner(indexes, y[indexes])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:38:5'): the model structure is correct ──────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3) at test_coBC.R:38:5
2. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
3. └─ssc (local) gen.learner(indexes, y[indexes])
4. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
5. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:50:5'): x can be a data.frame ───────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:50:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = as.data.frame(wine$xtrain), y = wine$ytrain, learner = knn3)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:60:5'): y can be a vector ───────────────────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:60:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$xtrain, y = as.vector(wine$ytrain), learner = knn3)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:70:5'): x.inst can be coerced to logical ────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:70:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, x.inst = TRUE, learner = knn3)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:120:5'): x is a square matrix when x.inst is FALSE ──────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:120:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$dtrain, y = wine$ytrain, x.inst = FALSE, learner = knn3)
5. └─ssc::coBCG(y, gen.learner1, gen.pred1, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(...)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:136:5'): max.iter is a value greather than 0 ────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:136:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3, max.iter = 80)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:152:5'): perc.full is a value between 0 and 1 ───────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:152:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3, perc.full = 0.8)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:169:5'): N is a value greather than 0 ───────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:169:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3, N = 2)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
── Error ('test_coBC.R:185:5'): u is a value greather than 0 ───────────────────
Error in `eval(code, test_env)`: object 'knn3' not found
Backtrace:
▆
1. ├─testthat::expect_is(...) at test_coBC.R:185:5
2. │ └─testthat::quasi_label(enquo(object), label)
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. └─ssc::coBC(x = wine$xtrain, y = wine$ytrain, learner = knn3, u = 80)
5. └─ssc::coBCG(y, gen.learner2, gen.pred2, N, perc.full, u, max.iter)
6. └─ssc (local) gen.learner(indexes, y[indexes])
7. └─ssc:::trainModel(x[training.ints, ], cls, learner, learner.pars)
8. └─base::do.call(learner, lpars)
[ FAIL 46 | WARN 5 | SKIP 3 | PASS 89 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc