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For Users

Installation and Configuration

check_aif_py_modules()
Check if all necessary python modules are available
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
prepare_session()
Function for setting up a python environment within R.
set_transformers_logger()
Sets the level for logging information of the 'transformers' library
update_aifeducation()
Updates an existing installation of 'aifeducation' on a machine

AI for Education Studio

start_aifeducation_studio()
Aifeducation Studio

Saving and Loading

load_from_disk()
Loading objects created with 'aifeducation'
save_to_disk()
Saving objects created with 'aifeducation'

Data Management

EmbeddedText
Abstract class for small data sets containing text embeddings
LargeDataSetForText
Abstract class for large data sets containing raw texts
LargeDataSetForTextEmbeddings
Abstract class for large data sets containing text embeddings

Base Models and Transformers

AIFETrType
Transformer types
aife_transformer.make()
Make a transformer

Text Embedding Models

TEFeatureExtractor
Feature extractor for reducing the number for dimensions of text embeddings.
TextEmbeddingModel
Text embedding model

Classification models based on text embeddings

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
TEClassifierSequential
Text embedding classifier with a neural net
TEClassifierSequentialPrototype
Text embedding classifier with a ProtoNet

Oversampling Approaches

knnor()
K-Nearest Neighbor OveRsampling approach (KNNOR)

Performance Measures

calc_standard_classification_measures()
Calculate recall, precision, and f1-scores
cohens_kappa()
Calculate Cohen's Kappa
fleiss_kappa()
Calculate Fleiss' Kappa
get_coder_metrics()
Calculate reliability measures based on content analysis
gwet_ac()
Calculate Gwet's AC1 and AC2
kendalls_w()
Calculate Kendall's coefficient of concordance w
kripp_alpha()
Calculate Krippendorff's Alpha

For Developers

R6 Classes (except transformers)

AIFEBaseModel
Base class for models using neural nets
ClassifiersBasedOnTextEmbeddings
Abstract class for all classifiers that use numerical representations of texts instead of words.
LargeDataSetBase
Abstract base class for large data sets
ModelsBasedOnTextEmbeddings
Base class for models using neural nets
TEClassifiersBasedOnProtoNet
Base class for classifiers relying on numerical representations of texts instead of words that use the architecture of Protonets and its corresponding training techniques.
TEClassifiersBasedOnRegular
Base class for regular classifiers relying on EmbeddedText or LargeDataSetForTextEmbeddings as input

R6 Classes for Data Management

DataManagerClassifier
Data manager for classification tasks

R6 Classes for Language Models/Transformers

.AIFEBaseTransformer
Base R6 class for creation and definition of .AIFE*Transformer-like classes
.AIFEBertTransformer
Child R6 class for creation and training of BERT transformers
.AIFEFunnelTransformer
Child R6 class for creation and training of Funnel transformers
.AIFELongformerTransformer
Child R6 class for creation and training of Longformer transformers
.AIFEMpnetTransformer
Child R6 class for creation and training of MPNet transformers
.AIFERobertaTransformer
Child R6 class for creation and training of RoBERTa transformers

Functions for Loading

aife_transformer.load_model_mlm()
Load a MLM-model
aife_transformer.load_tokenizer()
Load a tokenizer
.AIFEModernBertTransformer
Child R6 class for creation and training of ModernBERT transformers

Utils for Transformers

calc_tokenizer_statistics()
Estimate tokenizer statistics

Oversampling Approaches

knnor_is_same_class()
Validate a new point

Parameter Management

get_called_args()
Called arguments
get_depr_obj_names()
Get names of deprecated objects
get_magnitude_values()
Magnitudes of an argument
get_param_def()
Definition of an argument
get_param_dict()
Get dictionary of all parameters
get_param_doc_desc()
Description of an argument
get_TEClassifiers_class_names()
Get names of classifiers

File Management

create_dir()
Create directory if not exists
get_file_extension()
Get file extension

Utils General

auto_n_cores()
Number of cores for multiple tasks
create_object()
Create object
create_synthetic_units_from_matrix()
Create synthetic units
generate_id()
Generate ID suffix for objects
get_n_chunks()
Get the number of chunks/sequences for each case
get_synthetic_cases_from_matrix()
Create synthetic cases for balancing training data
matrix_to_array_c()
Reshape matrix to array
tensor_to_matrix_c()
Transform tensor to matrix
to_categorical_c()
Transforming classes to one-hot encoding

Utils Documentation

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 article
get_desc_for_core_model_architecture()
Generate documentation for core models
get_layer_documentation()
Generate layer documentation
get_parameter_documentation()
Generate layer documentation

Utils Python

get_py_package_version()
Get versions of a specific python package
get_py_package_versions()
Get versions of python components
load_all_py_scripts()
Load and re-load all python scripts
load_py_scripts()
Load and re-load python scripts
run_py_file()
Run python file

Utils Python for Data Management

class_vector_to_py_dataset()
Convert class vector to arrow data set
data.frame_to_py_dataset()
Convert data.frame to arrow data set
get_batches_index()
Assign cases to batches
prepare_r_array_for_dataset()
Convert R array for arrow data set
py_dataset_to_embeddings()
Convert arrow data set to an arrow data set
reduce_to_unique()
Reduce to unique cases
tensor_list_to_numpy()
Convert list of tensors into numpy arrays
tensor_to_numpy()
Tensor_to_numpy

Utils Logging

cat_message()
Print message (cat())
clean_pytorch_log_transformers()
Clean pytorch log of transformers
output_message()
Print message
print_message()
Print message (message())
read_log()
Function for reading a log file in R
read_loss_log()
Function for reading a log file containing a record of the loss during training.
reset_log()
Function that resets a log file.
reset_loss_log()
Reset log for loss information
write_log()
Write log

Utils Sustainability Tracking

get_alpha_3_codes()
Country Alpha 3 Codes

Utils Argument Checks

check_all_args()
Check arguments automatically
check_class_and_type()
Check class and type

Utils for AI for Education Studio

add_missing_args()
Add missing arguments to a list of arguments
long_load_target_data()
Load target data for long running tasks
summarize_args_for_long_task()
Summarize arguments from shiny input

Utils Test of the Package

check_adjust_n_samples_on_CI()
Set sample size for argument combinations
generate_args_for_tests()
Generate combinations of arguments
generate_embeddings()
Generate test embeddings
generate_tensors()
Generate test tensors
get_current_args_for_print()
Print arguments
get_fixed_test_tensor()
Generate static test tensor
get_test_data_for_classifiers()
Get test data
random_bool_on_CI()
Random bool on Continuous Integration