October 24, 2022
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- Prepended S4Vectors:: to mcols calls where necessary for it to work on Windows when multiple cores are used.

Dario Strbenac authored on 24/10/2022 10:20:07
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- Updated developer names. - Result object creation fixed when a subset of cross-validations have an error.

Dario Strbenac authored on 24/10/2022 01:45:06
October 20, 2022
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Remaining classifiers which don't name predictions have been made to name them.

Dario Strbenac authored on 20/10/2022 11:00:04
October 19, 2022
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- For each predict wrapper, the row names of the scores table or the names of the class vector now have sample IDs to make the output compatible with prevalidation. - XGBoost prediction function ensures that order of variables of test data table is the same as the variables used in model fitting.

Dario Strbenac authored on 19/10/2022 11:30:03
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- XGBoost scores columns have class labels now. - nFeatures cleaning now only done once in crossValidate and not unnecessarily doubled in CV (it changes vector into list).

Dario Strbenac authored on 19/10/2022 01:30:03
October 18, 2022
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- Corrected prepareData when useFeatures is "all". - runTests outcome variable has0 name same for all methods to fix the generic dispatching.

Dario Strbenac authored on 18/10/2022 01:45:10
October 17, 2022
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- Minor fixes.

Dario Strbenac authored on 17/10/2022 03:30:05
October 14, 2022
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- Random survival forest now has ranking and feature selection extractor function rfsrcFeatures. - Ranger random forest simple parameter set now has num.trees range to optimise, analogous to ntree in other packages.

Dario Strbenac authored on 14/10/2022 10:00:04
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- Minor fixes to standalone train and predict functions for list of inputs.

Dario Strbenac authored on 14/10/2022 06:45:03
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- Typo in train.DataFrame variable fixed. - .predict for DLDA made renamed to DLDA to enable easy dispatch by predict method. - randomForest wrapper now uses ranger as the underlying package instead of randomForest.

Dario Strbenac authored on 14/10/2022 00:30:12
October 12, 2022
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- Extreme gradient boosting wrapper added in interfaceXGB.R. - crossValidate gains performanceType parameter that defaults to "auto" which chooses depending on classification or survival task or can be set to any user-specified performance metric. - SelectParams default performanceType is now balanced accuracy, for consistency with other functions. - Vignette text updated to refer to balanced accuracy and to add k-NN and XGB classifiers to classifier table. - NEWS file updated for upcoming Bioconductor release.

Dario Strbenac authored on 12/10/2022 13:05:23
September 28, 2022
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- Tweaks to colCoxTests documentation to fix the last couple of warnings.

Dario Strbenac authored on 28/09/2022 12:10:03
September 27, 2022
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- crossValidate works with selectionMehod being none.

Dario Strbenac authored on 27/09/2022 01:26:02
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- plotFeatureClasses now works if classes is column name of data frame. - prepareData warning for variable name conversion for modelling.

Dario Strbenac authored on 27/09/2022 00:50:16
September 21, 2022
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- Fixed a couple of variable name typos. - Previous commit did not do variable name extraction correctly when getFeatures was not being used. Now it is done correctly regardless whether the variables are extracted from trained model (possibly already subsetted) or from feature selection (corresponding to original set of features).

Dario Strbenac authored on 21/09/2022 07:00:05