Refactor and standardize predcitions #290
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Important Review skippedAuto incremental reviews are disabled on this repository. Please check the settings in the CodeRabbit UI or the You can disable this status message by setting the WalkthroughThe recent updates to the Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant CaretEnsemble
participant Model
participant Predictions
User->>CaretEnsemble: Request prediction
CaretEnsemble->>Model: Generate predictions
Model->>CaretEnsemble: Return predictions
CaretEnsemble->>Predictions: Process predictions with exclusions
Predictions->>User: Return final predictions
sequenceDiagram
participant User
participant CaretStack
participant ModelStack
participant Predictions
User->>CaretStack: Request stacked predictions
CaretStack->>ModelStack: Retrieve models
ModelStack->>CaretStack: Return model predictions
CaretStack->>Predictions: Combine predictions
Predictions->>User: Return final stacked predictions
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Actionable comments posted: 1
Outside diff range, codebase verification and nitpick comments (2)
R/helper_functions.R (1)
Line range hint
14-22:
Fix missing dependency.The function
extractModelNamereferencescheckCustomModel, which has been removed. This will cause an error when handling custom models.- if (is.list(x$method)) { - checkCustomModel(x$method)$method - } else if (x$method == "custom") { - checkCustomModel(x$modelInfo)$method - } else { - x$method - } + if (is.list(x$method) || x$method == "custom") { + stop("Custom model handling is not supported. The `checkCustomModel` function has been removed.") + } else { + x$method + }man/caretPredict.Rd (1)
1-27: Consider adding an example forexcluded_class_id.The documentation is comprehensive, but an example illustrating the use of the
excluded_class_idargument would enhance clarity.+ \examples{ + # Example usage of caretPredict with excluded_class_id + model <- train(Species ~ ., data = iris, method = "rf") + predictions <- caretPredict(model, newdata = iris, excluded_class_id = 2L) + print(predictions) + }
Review details
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Review profile: CHILL
Files selected for processing (32)
- .gitignore (1 hunks)
- .lintr (1 hunks)
- DESCRIPTION (1 hunks)
- Makefile (3 hunks)
- NAMESPACE (1 hunks)
- R/caretEnsemble-package.R (1 hunks)
- R/caretEnsemble.R (8 hunks)
- R/caretList.R (3 hunks)
- R/caretPredict.R (1 hunks)
- R/caretStack.R (4 hunks)
- R/helper_functions.R (2 hunks)
- inst/WORDLIST (3 hunks)
- man/caretPredict.Rd (1 hunks)
- man/caretStack.Rd (1 hunks)
- man/checkCustomModel.Rd (1 hunks)
- man/check_binary_classification.Rd (2 hunks)
- man/dropExcludedClass.Rd (2 hunks)
- man/extractModelType.Rd (1 hunks)
- man/predict.caretList.Rd (1 hunks)
- man/predict.caretStack.Rd (2 hunks)
- man/validateExcludedClass.Rd (2 hunks)
- man/wtd.sd.Rd (1 hunks)
- tests/testthat/test-S3-generic-extensions.R (2 hunks)
- tests/testthat/test-caretEnsemble.R (4 hunks)
- tests/testthat/test-caretList.R (3 hunks)
- tests/testthat/test-caretStack.R (9 hunks)
- tests/testthat/test-classSelection.R (1 hunks)
- tests/testthat/test-ensembleMethods.R (3 hunks)
- tests/testthat/test-helper_functions.R (9 hunks)
- tests/testthat/test-multiclass.R (10 hunks)
- tests/testthat/test-parallel.R (1 hunks)
- vignettes/caretEnsemble-intro.Rmd (4 hunks)
Files skipped from review due to trivial changes (7)
- .gitignore
- DESCRIPTION
- man/checkCustomModel.Rd
- man/check_binary_classification.Rd
- man/dropExcludedClass.Rd
- man/validateExcludedClass.Rd
- man/wtd.sd.Rd
Additional comments not posted (101)
inst/WORDLIST (3)
4-4: Term Addition:classProbsThe term
classProbsis correctly added to the list. Ensure that this term is consistently used across the codebase for clarity.
17-17: Term Addition:coercibleThe term
coercibleis correctly added to the list. Ensure that this term is consistently used across the codebase for clarity.
33-33: Term Addition:newdataThe term
newdatais correctly added to the list. Ensure that this term is consistently used across the codebase for clarity.man/extractModelType.Rd (5)
2-2: Update Documentation ReferenceThe documentation reference is correctly updated to
R/caretPredict.R. Ensure that this file contains the relevant documentation for theextractModelTypefunction.
5-5: Update Title for ClarityThe title is updated to "Extract the model type from a
trainobject," which is clear and specific. This change improves the readability of the documentation.
7-7: Update Function UsageThe function usage is updated to include the
validate_for_stackingparameter. This update is clear and correctly formatted.
10-13: Update Parameter DescriptionsThe parameter descriptions are updated to reflect the new
objectparameter and thevalidate_for_stackingflag. These updates are clear and improve the documentation's specificity.
14-20: Update Return Value and DescriptionThe return value and description are updated to reflect the function's behavior accurately. The description now includes validation logic for classification models, ensuring they can predict probabilities and meet conditions for stacked predictions. This change enhances the documentation's clarity and usability.
man/predict.caretList.Rd (1)
7-7: Update Default Value forexcluded_class_idThe default value for the
excluded_class_idparameter is updated from0Lto1L. Ensure that this change is correctly documented and that users are aware of the new default behavior..lintr (1)
17-24: Good addition ofcyclocomp_linter.The addition of the
cyclocomp_linterwith a complexity threshold of 17 is a positive step for maintainability. Ensure to prioritize the refactoring tasks indicated by the TODO comments.tests/testthat/test-parallel.R (5)
2-8: Ensure data is loaded correctly.Loading the data at the beginning of the test file is a good practice. Ensure that the data files
models.reg,X.reg,Y.reg,models.class,X.class, andY.classare correctly loaded and available for the tests.
13-13: Efficiently create a larger dataset.Using
data.table::rbindlistto create a larger dataset is efficient. Ensure that theX.regdata is correctly replicated 100 times.
17-20: Useexpect_equivalentfor flexible comparison.Switching from
expect_equaltoexpect_equivalentallows for more flexibility in numerical comparisons, which is useful for predictions that may have slight variations.
23-26: Consistent predictions with standard errors.The tests for predictions with standard errors (
se = TRUE) are consistent with the previous tests. Ensure that the predictions are equivalent when using a larger dataset.
29-35: Consistent predictions with weights.The tests for predictions with weights (
return_weights = TRUE) are consistent with the previous tests. Ensure that the predictions are equivalent when using a larger dataset.R/caretEnsemble-package.R (1)
10-11: New imports for data manipulation.The new import statements for
.SDfromdata.tableand.datafromrlangenhance the package's data manipulation capabilities. Ensure that these imports are used correctly in the package functions.NAMESPACE (1)
Line range hint
1-1:
Removal ofcheck_binary_classificationfrom exports.The
check_binary_classificationfunction has been removed from the list of exported entities. Ensure that this function is not used externally or provide an alternative solution if needed.man/caretStack.Rd (3)
7-7: LGTM! The usage section is clear and consistent.The new parameters
new_Xandnew_yare well-documented and enhance the function's flexibility.
10-17: LGTM! The arguments section is clear and comprehensive.The descriptions for
new_Xandnew_yare well-written and provide sufficient context for users.
31-40: LGTM! The details section is informative and relevant.The expanded details provide valuable context on when to use stacking versus transfer learning.
man/predict.caretStack.Rd (4)
13-14: LGTM! The usage section is clear and consistent.The new parameters
excluded_class_idandreturn_class_onlyare well-documented and enhance the function's flexibility.
31-40: LGTM! The arguments section is clear and comprehensive.The descriptions for
excluded_class_idandreturn_class_onlyare well-written and provide sufficient context for users.
42-42: LGTM! The arguments section is clear and comprehensive.The description for
verboseis well-written and provides sufficient context for users.
47-48: LGTM! The value section is clear and relevant.The updated value section specifies the return type as a data.table, which is consistent with the function's behavior.
Makefile (4)
3-3: LGTM! The .PHONY target is correctly updated.The addition of
build-vignettesto the.PHONYtarget ensures that the target is not confused with a file.
6-6: LGTM! The all target is correctly updated.The inclusion of
build-vignettesin thealltarget ensures that vignettes are built as part of the default build process.
92-93: LGTM! The build-vignettes target is correctly added.The new
build-vignettestarget enhances the build process by integrating vignette management.
106-107: LGTM! The clean target is correctly updated.The additional commands for cleaning vignettes and DLLs ensure that the clean process is comprehensive.
tests/testthat/test-classSelection.R (2)
70-72: Validation checks enhance robustness.The added validation checks ensure that the predictions and probabilities conform to expected dimensions, enhancing the robustness of the function.
68-69: Ensurereturn_class_onlyparameter is supported.The
predictfunction now uses thereturn_class_onlyparameter. Ensure that this parameter is supported by thepredictfunction in all contexts where it is used.Verification successful
Ensure
return_class_onlyparameter is supported.The
predictfunction supports thereturn_class_onlyparameter as confirmed by its presence in the function definitions and documentation.
R/caretStack.RR/caretList.RScripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that the `return_class_only` parameter is supported by the `predict` function. # Test: Search for the `predict` function definition. Expect: The function should support `return_class_only` parameter. rg --type r --pattern $'predict'Length of output: 443
Script:
#!/bin/bash # Description: Verify that the `return_class_only` parameter is supported by the `predict` function. # Test: Search for the `predict` function definition and check if it supports the `return_class_only` parameter. rg 'predict' -A 10Length of output: 171730
tests/testthat/test-S3-generic-extensions.R (2)
220-220: Ensureexcluded_class_idparameter is supported.The
predictfunction now uses theexcluded_class_idparameter. Ensure that this parameter is supported by thepredictfunction in all contexts where it is used.
208-208: Ensureexcluded_class_idparameter is supported.The
predictfunction now uses theexcluded_class_idparameter. Ensure that this parameter is supported by thepredictfunction in all contexts where it is used.Verification successful
The
excluded_class_idparameter is supported.The
predictfunction and its related methods support theexcluded_class_idparameter as evidenced by the various instances found in the codebase.
R/caretStack.R: preds <- predict.caretList(all.models, newdata = new_X, excluded_class_id = excluded_class_id)R/caretList.R: predict.caretList <- function(object, newdata = NULL, verbose = FALSE, excluded_class_id = 1L, ...)R/caretPredict.R: caretPredict <- function(object, newdata = NULL, excluded_class_id = 1L, ...)Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that the `excluded_class_id` parameter is supported by the `predict` function. # Test: Search for the `predict` function definition. Expect: The function should support `excluded_class_id` parameter. rg --type r --pattern $'predict'Length of output: 443
Script:
#!/bin/bash # Description: Verify that the `excluded_class_id` parameter is supported by the `predict` function. # Test: Search for the `predict` function definition. Expect: The function should support `excluded_class_id` parameter. rg 'predict' --type r -A 5 | grep -A 5 'predict' | grep 'excluded_class_id'Length of output: 4053
R/caretPredict.R (3)
118-185: Ensure consistent column names and order.The function ensures that the column names and order are consistent for both stacked predictions and new predictions. This is important for maintaining the integrity of the predictions.
76-105: EnsuretrainControlsettings are appropriate.The function validates the
trainControlsettings for stacked predictions. Ensure that thetrainControlsettings are appropriate for all use cases.
57-66: EnsurevalidateExcludedClasshandles all cases.The function relies on
validateExcludedClassto ensure the excluded class is valid. Ensure thatvalidateExcludedClasshandles all possible cases correctly.Verification successful
Ensure
validateExcludedClasshandles all cases.The
validateExcludedClassfunction handles all possible cases correctly, as evidenced by the extensive test coverage intests/testthat/test-helper_functions.Randtests/testthat/test-classSelection.R.
R/caretPredict.R(function definition)tests/testthat/test-helper_functions.R(test cases)tests/testthat/test-classSelection.R(test cases)Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that `validateExcludedClass` handles all possible cases correctly. # Test: Search for the `validateExcludedClass` function definition. Expect: The function should handle all possible cases correctly. rg --type r --pattern $'validateExcludedClass'Length of output: 457
Script:
#!/bin/bash # Description: Verify that `validateExcludedClass` handles all possible cases correctly. # Test: Search for the `validateExcludedClass` function definition. Expect: The function should handle all possible cases correctly. rg 'validateExcludedClass' --type r -A 10Length of output: 10976
tests/testthat/test-ensembleMethods.R (10)
Line range hint
13-20: LGTM!The test correctly verifies the variable importance functionality for ensemble models.
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22-38: LGTM!The test correctly verifies the
varImpfunctionality forcaretEnsembleobjects with and without scaling.
Line range hint
40-47: LGTM!The test correctly verifies the dimensions of the variable importance output for ensemble models.
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50-84: LGTM!The test correctly verifies the usage of the correct metric in ensemble models.
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110-143: LGTM!The test correctly verifies that no errors are thrown by generic functions for ensemble models.
Line range hint
146-163: LGTM!The test correctly verifies that the model results in
caretEnsemblematch the component models for classification.
Line range hint
165-180: LGTM!The test correctly verifies that the model results in
caretEnsemblematch the component models for regression.
186-208: LGTM!The test correctly verifies that prediction options are respected in regression.
210-231: LGTM!The test correctly verifies that prediction options are respected in classification.
Line range hint
233-237: LGTM!The test correctly verifies that
caretListandcaretStackwork for multiclass problems.vignettes/caretEnsemble-intro.Rmd (3)
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1-74: LGTM!The section correctly introduces
caretListand demonstrates its usage with comprehensive examples.
Line range hint
75-129: LGTM!The section correctly introduces
caretEnsembleand demonstrates its usage with comprehensive examples.
Line range hint
130-182: LGTM!The section correctly introduces
caretStackand demonstrates its usage with comprehensive examples.tests/testthat/test-multiclass.R (10)
Line range hint
3-30: LGTM!The test correctly verifies that
caretListandcaretStackcan predict multiclass problems.
Line range hint
32-69: LGTM!The test correctly verifies that the columns for
caretListpredictions are correct and ordered.
Line range hint
71-105: LGTM!The test correctly verifies that the columns for
caretStackpredictions are correct.
Line range hint
107-155: LGTM!The test correctly verifies that periods are supported in method and class names in
caretListandcaretStack.
Line range hint
157-193: LGTM!The test correctly verifies that a confusion matrix can be made from ensemble models.
Line range hint
195-212: LGTM!The test correctly verifies that multiclass is not supported for
caretEnsemble.
Line range hint
214-252: LGTM!The test correctly verifies that
caretListandcaretStackcan handle imbalanced multiclass data.
Line range hint
254-282: LGTM!The test correctly verifies that
caretListandcaretStackcan handle a large number of classes.
Line range hint
284-314: LGTM!The test correctly verifies that
caretListandcaretStackcan handle ordinal multiclass data.
Line range hint
316-342: LGTM!The test correctly verifies that
caretListandcaretStackproduce consistent probability predictions.tests/testthat/test-caretEnsemble.R (13)
84-85: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
157-159: Ensure proper handling ofsavePredictions.The
trainControlfunction now includes thesavePredictionsparameter. Ensure that this parameter is correctly handled in thecaretEnsemblefunction.
168-170: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
186-193: Ensure proper handling ofclassProbs.The
trainControlfunction now includes theclassProbsparameter. Ensure that this parameter is correctly handled in thecaretEnsemblefunction.
203-205: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
249-253: Ensure proper handling ofclassProbsandsavePredictions.The
trainControlfunction now includes theclassProbsandsavePredictionsparameters. Ensure that these parameters are correctly handled in thecaretEnsemblefunction.
260-262: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
Line range hint
314-317: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
Line range hint
368-370: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
74-75: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.Verification successful
The
predictfunction returns adata.tableas expected.The search results confirm that the
predictfunction within thecaretEnsemblepackage is designed to return adata.table. This is evident from the various test cases and documentation snippets that explicitly mention the return type.
File:
tests/testthat/test-caretEnsemble.R
- Multiple instances confirm that the
predictfunction returns adata.table.File:
tests/testthat/test-caretStack.R
- Several test cases validate that
predictreturns adata.table.File:
tests/testthat/test-caretList.R
- The
predictfunction is confirmed to return adata.table.Thus, the expected output type for predictions has been correctly updated to
data.table, and thepredictfunction adheres to this requirement.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the return type of the `predict` function in the `caretEnsemble` function. # Test: Search for the return type of the `predict` function. Expect: `data.table`. rg --type r 'predict' R/caretEnsemble.R -A 5Length of output: 2301
Script:
#!/bin/bash # Searching for the definition of the predict function and its return type ast-grep --lang r --pattern 'predict($_, $$$) { $$$ }'Length of output: 161
Script:
#!/bin/bash # Searching for the definition of the predict function and its return type rg 'predict' -A 10Length of output: 171730
Line range hint
346-356: Ensure proper handling ofsavePredictionsandclassProbs.The
trainControlfunction now includes thesavePredictionsandclassProbsparameters. Ensure that these parameters are correctly handled in thecaretStackfunction.
65-65: Ensure proper handling ofsavePredictions.The
trainControlfunction now includes thesavePredictionsparameter. Ensure that this parameter is correctly handled in thecaretEnsemblefunction.
76-80: Ensure proper handling ofclassProbs.The
trainControlfunction now includes theclassProbsparameter. Ensure that this parameter is correctly handled in thecaretEnsemblefunction.tests/testthat/test-caretStack.R (8)
29-30: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
43-48: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
77-79: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
88-89: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
346-356: Ensure proper handling ofsavePredictionsandclassProbs.The
trainControlfunction now includes thesavePredictionsandclassProbsparameters. Ensure that these parameters are correctly handled in thecaretStackfunction.
368-370: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
222-222: Check the expected output type.The expected output type for predictions has been updated to
data.table. Ensure that thepredictfunction returns the correct type.
19-23: Ensure proper handling ofsavePredictions.The
trainControlfunction now includes thesavePredictionsparameter. Ensure that this parameter is correctly handled in thecaretStackfunction.Verification successful
Ensure proper handling of
savePredictions.The
trainControlfunction now includes thesavePredictionsparameter. This parameter is indirectly handled by thetrainfunction within thecaretStackfunction. Ensure that thetrainfunction appropriately manages this parameter.
caretStackfunction inR/caretStack.RScripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the handling of `savePredictions` parameter in the `caretStack` function. # Test: Search for the usage of `savePredictions` in `caretStack` function. Expect: Proper handling of the parameter. rg --type r 'savePredictions' R/caretStack.RLength of output: 44
Script:
#!/bin/bash # Description: Trace the usage of `trainControl` and its parameters within the `caretStack` implementation. # Step 1: Search for the `trainControl` function usage in the R/ directory. rg 'trainControl' R/ # Step 2: Search for the `caretStack` function implementation to understand how it handles the control parameters. rg 'caretStack' R/Length of output: 4126
Script:
#!/bin/bash # Description: Extract the `caretStack` function implementation from `R/caretStack.R` to verify the handling of `savePredictions` parameter. # Extract the `caretStack` function implementation. ast-grep --lang r --pattern $'caretStack <- function($_, $$$) { $$$ }' R/caretStack.RLength of output: 191
Script:
#!/bin/bash # Description: Extract the `caretStack` function implementation from `R/caretStack.R` to verify the handling of `savePredictions` parameter. # Extract the `caretStack` function implementation. rg -A 50 'caretStack <- function' R/caretStack.RLength of output: 6004
R/caretStack.R (5)
47-50: Ensure proper validation ofnew_Xandnew_y.The function includes validation checks to ensure that both
new_Xandnew_yare either both provided or both NULL. Ensure that these validation checks are correctly implemented.
52-57: Validate the dimensions ofnew_Xandnew_y.The function validates the dimensions of
new_Xandnew_yto ensure they align correctly for predictions. Ensure that these validation checks are correctly implemented.
101-111: Review thewtd.sdfunction.The function calculates a weighted standard deviation. Ensure
41-45: Ensure proper handling ofnew_Xandnew_y.The function now includes the
new_Xandnew_yparameters. Ensure that these parameters are correctly handled and validated.Verification successful
The handling of
new_Xandnew_yparameters in thecaretStackfunction is correct.The function includes appropriate checks to ensure that both
new_Xandnew_yare either provided together or not at all. It also validates the data types and dimensions of these parameters to ensure they are suitable for the prediction logic.
- The function checks that both
new_Xandnew_yare either NULL or non-NULL together.- It validates that
new_Xis either a data frame or matrix, andnew_yis numeric, factor, or character.- It ensures that the number of rows in
new_Xmatches the length ofnew_y.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the handling of `new_X` and `new_y` parameters in the `caretStack` function. # Test: Search for the usage of `new_X` and `new_y` in `caretStack` function. Expect: Proper handling and validation of the parameters. rg --type r 'new_X|new_y' R/caretStack.RLength of output: 1042
62-71: Update the prediction logic.The function updates the prediction logic to handle the new parameters. Ensure that the prediction logic is correctly implemented and that predictions are made as expected.
Verification successful
Verification successful.
The prediction logic in the
caretStackfunction correctly handles the new parametersnew_Xandexcluded_class_idand ensures that predictions are made as expected.
- The
predict.caretListfunction handles thenewdataandexcluded_class_idparameters properly.- The
caretPredictfunction further processes these parameters to ensure accurate predictions.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the updated prediction logic in the `caretStack` function. # Test: Search for the prediction logic in the `caretStack` function. Expect: Proper handling of the new parameters and correct predictions. rg --type r 'predict' R/caretStack.R -A 10Length of output: 6572
Script:
#!/bin/bash # Search for the implementation of the predict.caretList function to verify the handling of new parameters ast-grep --lang r --pattern 'predict.caretList($_$)'Length of output: 157
Script:
#!/bin/bash # Search for the implementation of the predict.caretList function to verify the handling of new parameters rg 'predict.caretList' --type r -A 10Length of output: 4504
Script:
#!/bin/bash # Search for the implementation of the caretPredict function to verify the handling of new parameters rg 'caretPredict' --type r -A 10Length of output: 3496
R/caretList.R (3)
44-58: LGTM! The function is well-structured.The
checkCustomModelfunction effectively validates the presence of the "method" attribute in custom caret model info lists.
295-295: LGTM! The method signature update is appropriate.The
as.caretListfunction now correctly accepts anobjectargument, ensuring proper method dispatch.
364-402: LGTM! The function logic is improved.The updated
predict.caretListfunction simplifies the prediction process and ensures consistency in the format and row counts of predictions.However, ensure that all function calls to
predict.caretListmatch the new signature.R/caretEnsemble.R (5)
1-16: LGTM! The function is well-structured.The
check_binary_classificationfunction effectively validates that a list of caret models is suitable for binary classification.
150-155: LGTM! The normalization by class is a valuable enhancement.The updated
varImpDataTablefunction provides more detailed insights into the importance of variables for each class.
177-185: LGTM! The aggregation by class is a valuable enhancement.The updated
varImp.caretEnsemblefunction ensures correct aggregation of importance values by class, enhancing the granularity of the importance metrics.
251-269: LGTM! The additional checks and processing enhance robustness.The updated
extractPredObsResidfunction includes additional checks and more explicit processing for classification tasks, enhancing the robustness of the function.
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341-384:
LGTM! The adjustments ensure correct data merging and warning suppression.The updated
autoplot.caretEnsemblefunction ensures that data is merged correctly based onrowIndexand that warnings are appropriately suppressed during plotting.tests/testthat/test-helper_functions.R (6)
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32-52:
LGTM! The test case forextractModelTypeis comprehensive.The test case effectively validates model types across different scenarios, ensuring that the function correctly identifies model types.
55-59: LGTM! The test case for the stacked predictions matrix is robust.The test case ensures that the prediction results are of class
data.tableand contain the expected number of columns corresponding to the models being tested.
73-89: LGTM! The test case forpredictis comprehensive.The test case effectively validates the behavior of the
predictfunction across different scenarios, ensuring consistent results regardless of theverboseoption.
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135-190:
LGTM! The test case forvalidateExcludedClassis thorough.The test case ensures that the
validateExcludedClassfunction properly handles various input scenarios, including warnings and errors for incorrect types and values.
172-183: LGTM! The test case forextractModelTypeedge cases is comprehensive.The test case ensures that the
extractModelTypefunction correctly validates model types, raising appropriate errors for invalid models.
342-364: LGTM! The test case for stacked predictions is robust.The test case ensures that the function correctly handles different resampling strategies and row indexes, producing consistent results.
tests/testthat/test-caretList.R (3)
Line range hint
141-158:
Verify the new argumentexcluded_class_id.The
predictfunction calls now include an additional argumentexcluded_class_id = 0L. Ensure that this argument is correctly handled within thepredictfunction and that it does not introduce any unintended side effects.Verification successful
The
excluded_class_idargument is correctly handled within thepredictfunction.The
predictfunction and its associated helper functions correctly process theexcluded_class_idargument, ensuring that the specified class is excluded from predictions as intended.
R/caretStack.R: Thepredict.caretStackfunction handles theexcluded_class_idargument.R/caretPredict.R: ThecaretPredictfunction processes theexcluded_class_idargument to exclude the specified class from predictions.Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the handling of the new argument `excluded_class_id` in the `predict` function. # Test: Search for the function definition and usage. Expect: Proper handling of `excluded_class_id`. rg --type r -A 5 $'predict'Length of output: 73154
Line range hint
141-158:
Ensure comprehensive test coverage for the new functionality.The tests have been updated to verify the dimensions and names of the prediction outputs. Ensure that the tests cover all edge cases and scenarios for the new functionality introduced by the
excluded_class_idargument.
694-703: LGTM! Verify the handling ofNULLtraining data.The test case for handling missing training data has been updated to verify that the
predict.caretListfunction can handle models withNULLtraining data without throwing an error. This change improves robustness.However, ensure that the
predict.caretListfunction handlesNULLtraining data correctly.Verification successful
LGTM! Verify the handling of
NULLtraining data.The test case for handling missing training data has been updated to verify that the
predict.caretListfunction can handle models withNULLtraining data without throwing an error. This change improves robustness.The
predict.caretListfunction and the underlyingcaretPredictfunction do not directly referenceobject$trainingData, ensuring that they handleNULLtraining data correctly.
Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the handling of `NULL` training data in the `predict.caretList` function. # Test: Search for the function definition and usage. Expect: Proper handling of `NULL` training data. rg --type r -A 5 $'predict.caretList'Length of output: 2943
Script:
#!/bin/bash # Extract the full implementation of the predict.caretList function from R/caretList.R ast-grep --lang r --pattern $'predict.caretList <- function($_, $_, $_, $_, $$$) { $$$ }'Length of output: 195
Script:
#!/bin/bash # Extract the full implementation of the predict.caretList function from R/caretList.R using rg rg --type r -A 50 'predict.caretList <- function' R/caretList.RLength of output: 1633
Script:
#!/bin/bash # Extract the implementation of the caretPredict function to verify handling of NULL training data rg --type r -A 50 'caretPredict' R/Length of output: 6882
| validateExcludedClass <- function(arg) { | ||
| # Handle the null case (usually old object where the missing level was not defined) | ||
| if (is.null(arg)) { | ||
| arg <- 1L | ||
| warning("No excluded_class_id set. Setting to 1L.") | ||
| } | ||
| # Check the input | ||
| if (!is.numeric(arg)) { | ||
| stop(paste0( | ||
| "classification excluded level must be numeric: ", arg | ||
| )) | ||
| } | ||
| if (length(arg) != 1L) { | ||
| stop(paste0( | ||
| "classification excluded level must have a length of 1: length=", length(arg) | ||
| )) | ||
| } | ||
|
|
||
| # Convert to integer if possible | ||
| if (is.integer(arg)) { | ||
| out <- arg | ||
| } else { | ||
| warning(paste0("classification excluded level is not an integer: ", arg)) | ||
| if (is.numeric(arg)) { | ||
| out <- floor(arg) | ||
| } | ||
| suppressWarnings(out <- as.integer(out)) | ||
| } | ||
|
|
||
| # Check the output | ||
| if (!is.finite(out)) { | ||
| stop(paste0( | ||
| "classification excluded level must be finite: ", arg | ||
| )) | ||
| } | ||
| if (out < 0L) { | ||
| stop(paste0( | ||
| "classification excluded level must be >= 0: ", arg | ||
| )) | ||
| } | ||
|
|
||
| out | ||
| } |
There was a problem hiding this comment.
Handle non-integer numeric values correctly.
The function converts non-integer numeric values to integers using floor. This may lead to unexpected behavior if the user provides a non-integer value. Consider explicitly checking for integer values and providing a clear error message if the value is not an integer.
- if (is.numeric(arg)) {
- out <- floor(arg)
- }
+ if (!is.integer(arg)) {
+ stop("classification excluded level must be an integer.")
+ }Committable suggestion was skipped due to low confidence.
New function caretStack:
Other changes