Man pages for aifeducation
Artificial Intelligence for Education
| add_missing_args | Add missing arguments to a list of arguments |
| AIFEBaseModel | Base class for objects using a pytorch model as core model. |
| AIFEMaster | Base class for most objects |
| auto_n_cores | Number of cores for multiple tasks |
| BaseModelBert | BERT-Transformer |
| BaseModelCore | Abstract class for all BaseModels |
| BaseModelDebertaV2 | DeBERTa V2 |
| BaseModelFunnel | Funnel transformer |
| BaseModelModernBert | ModernBert |
| BaseModelMPNet | MPNet |
| BaseModelRoberta | RoBERTa |
| BaseModelsIndex | List of all available BaseModels |
| build_documentation_for_model | Generate documentation for a classifier class |
| build_layer_stack_documentation_for_vignette | Generate documentation of all layers for an vignette or... |
| calc_standard_classification_measures | Calculate recall, precision, and f1-scores |
| calc_tokenizer_statistics | Estimate tokenizer statistics |
| cat_message | Print message ('cat()') |
| check_adjust_n_samples_on_CI | Set sample size for argument combinations |
| check_aif_py_modules | Check if all necessary python modules are available |
| check_all_args | Check arguments automatically |
| check_class_and_type | Check class and type |
| ClassifiersBasedOnTextEmbeddings | Abstract class for all classifiers that use numerical... |
| class_vector_to_py_dataset | Convert class vector to arrow data set |
| clean_pytorch_log_transformers | Clean pytorch log of transformers |
| cohens_kappa | Calculate Cohen's Kappa |
| create_config_state | Create config for R interfaces |
| create_data_embeddings_description | Generate description for text embeddings |
| create_dir | Create directory if not exists |
| create_object | Create object#' |
| create_synthetic_units_from_matrix | Create synthetic units |
| data.frame_to_py_dataset | Convert data.frame to arrow data set |
| DataManagerClassifier | Data manager for classification tasks |
| DataSetsIndex | List of all available types of data sets |
| doc_formula | Create rd formula |
| EmbeddedText | Abstract class for small data sets containing text embeddings |
| fleiss_kappa | Calculate Fleiss' Kappa |
| generate_args_for_tests | Generate combinations of arguments |
| generate_embeddings | Generate test embeddings |
| generate_id | Generate ID suffix for objects |
| generate_tensors | Generate test tensors |
| get_alpha_3_codes | Country Alpha 3 Codes |
| get_batches_index | Assign cases to batches |
| get_called_args | Called arguments |
| get_coder_metrics | Calculate reliability measures based on content analysis |
| get_current_args_for_print | Print arguments |
| get_depr_obj_names | Get names of deprecated objects |
| get_desc_for_core_model_architecture | Generate documentation for core models |
| get_dict_cls_type | Dictionary of classifier types |
| get_dict_core_models | Dictionary of core models |
| get_dict_input_types | Dictionary of input types |
| get_file_extension | Get file extension |
| get_fixed_test_tensor | Generate static test tensor |
| get_layer_dict | Dictionary of layers |
| get_layer_documentation | Generate layer documentation |
| get_magnitude_values | Magnitudes of an argument |
| get_n_chunks | Get the number of chunks/sequences for each case |
| get_param_def | Definition of an argument |
| get_param_dict | Get dictionary of all parameters |
| get_param_doc_desc | Description of an argument |
| get_parameter_documentation | Generate layer documentation |
| get_py_package_version | Get versions of a specific python package |
| get_py_package_versions | Get versions of python components |
| get_recommended_py_versions | Recommended version of python packages |
| get_synthetic_cases_from_matrix | Create synthetic cases for balancing training data |
| get_TEClassifiers_class_names | Get names of classifiers |
| get_test_data_for_classifiers | Get test data |
| get_time_stamp | Time stamp |
| gwet_ac | Calculate Gwet's AC1 and AC2 |
| HuggingFaceTokenizer | HuggingFaceTokenizer |
| imdb_movie_reviews | Standford Movie Review Dataset |
| inspect_tmp_dir | Inspect Temporary directory |
| install_aifeducation | Install aifeducation on a machine |
| install_aifeducation_studio | Install 'AI for Education - Studio' on a machine |
| install_py_modules | Installing necessary python modules to an environment |
| kendalls_w | Calculate Kendall's coefficient of concordance w |
| knnor | K-Nearest Neighbor OveRsampling approach (KNNOR) |
| knnor_is_same_class | Validate a new point |
| kripp_alpha | Calculate Krippendorff's Alpha |
| LargeDataSetBase | Abstract base class for large data sets |
| LargeDataSetForText | Abstract class for large data sets containing raw texts |
| LargeDataSetForTextEmbeddings | Abstract class for large data sets containing text embeddings |
| License_Server | Server function for: graphical user interface for showing the... |
| load_all_py_scripts | Load and re-load all python scripts |
| load_from_disk | Loading objects created with 'aifeducation' |
| load_py_scripts | Load and re-load python scripts |
| long_load_target_data | Load target data for long running tasks |
| matrix_to_array_c | Reshape matrix to array |
| ModelsBasedOnTextEmbeddings | Base class for models using neural nets |
| monitor_test_time_on_CI | Print duration of a test on CI |
| output_message | Print message |
| prepare_r_array_for_dataset | Convert R array for arrow data set |
| prepare_session | Function for setting up a python environment within R. |
| print_message | Print message ('message()') |
| py_dataset_to_embeddings | Convert arrow data set to an arrow data set |
| random_bool_on_CI | Random bool on Continuous Integration |
| read_log | Function for reading a log file in R |
| read_loss_log | Function for reading a log file containing a record of the... |
| reduce_to_unique | Reduce to unique cases |
| Reliability_Server | Server function for: graphical user interface for displaying... |
| Reliability_UI | Graphical user interface for displaying the reliability of... |
| reset_log | Function that resets a log file. |
| reset_loss_log | Reset log for loss information |
| run_py_file | Run python file |
| save_to_disk | Saving objects created with 'aifeducation' |
| set_transformers_logger | Sets the level for logging information of the 'transformers'... |
| start_aifeducation_studio | Aifeducation Studio |
| summarize_args_for_long_task | Summarize arguments from shiny input |
| summarize_tracked_sustainability | Summarizing tracked sustainability data |
| TEClassifierParallel | Text embedding classifier with a neural net |
| TEClassifierParallelPrototype | Text embedding classifier with a ProtoNet |
| TEClassifierProtoNet | Text embedding classifier with a ProtoNet |
| TEClassifierRegular | Text embedding classifier with a neural net |
| TEClassifiersBasedOnProtoNet | Base class for classifiers relying on numerical... |
| TEClassifiersBasedOnRegular | Base class for regular classifiers relying on EmbeddedText or... |
| TEClassifierSequential | Text embedding classifier with a neural net |
| TEClassifierSequentialPrototype | Text embedding classifier with a ProtoNet |
| TEFeatureExtractor | Feature extractor for reducing the number for dimensions of... |
| tensor_list_to_numpy | Convert list of tensors into numpy arrays |
| tensor_to_matrix_c | Transform tensor to matrix |
| tensor_to_numpy | Tensor_to_numpy |
| TextEmbeddingModel | Text embedding model |
| to_categorical_c | Transforming classes to one-hot encoding |
| TokenizerBase | Base class for tokenizers |
| TokenizerIndex | List of all available Tokenizers |
| update_aifeducation | Updates an existing installation of 'aifeducation' on a... |
| WordPieceTokenizer | WordPieceTokenizer |
| write_log | Write log |
