| addFactorLevel | Add a new level to a factor |
| cleanData | Clean training and test data sets |
| countNAs | Count the number of NAs in each column of a data frame |
| createConfigFile | Create configuration file for a data set |
| createDateFeatures | Create new features based on date fields |
| fitFinalModel | Fit all training data using the best model with optimized... |
| fixDataRepresentation | Change the data representation depending to fit requirements... |
| fix_factor_levels | Synchronize factor levels between train and test sets |
| getEvaluation | Predict and evaluate performance of a machine learning model |
| getModel | Get an optimized machine learning model |
| getModelList | Get a list of models to fit |
| getModelMatrix | Convert a data frame to a model matrix |
| getNumClass | Find the number of different classes in labels. |
| getPartitionIndex | Get partition index for training and validation sets |
| getPreProcFactor | Preprocess all factor columns of a data frame |
| getPreProcNumeric | Preprocess all numeric columns of a data frame |
| getSingleValueCols | Find data frame columns where all values are the same |
| getSparseMatrix | Convert a data frame to a sparse model matrix |
| getSubmission | Create submission data frame |
| getTaskParams | Get task specific parameters |
| identifyTask | Identify the type of the learning task |
| imputeDefault | Impute missing values with default values |
| imputeNA | Impute missing values in a column or vector |
| imputeNAs | Impute missing values in train or test data set |
| imputeValue | Replace NAs with a specific value |
| isBetter | Check if the new score is better than the current best score |
| processText | Preprocess all character columns of a data frame |
| selectModel | Select the best performing model |
| splitData | Split data to training and validation sets |
| updateBestModel | Update best_fit_model if the new model is better than the... |
| update_classes | Change classes in a data frame according to configuration... |
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