Package index • aifeducation

Installation and Configuration

check_aif_py_modules(): Check if all necessary python modules are available

install_aifeducation(): Install aifeducation on a machine

install_py_modules(): Installing necessary python modules to an environment

set_transformers_logger(): Sets the level for logging information of the 'transformers' library

Tensorflow only

set_config_cpu_only(): Setting cpu only for 'tensorflow'

set_config_gpu_low_memory(): Setting gpus' memory usage

set_config_os_environ_logger(): Sets the level for logging information in tensorflow

set_config_tf_logger(): Sets the level for logging information in tensorflow

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

DataManagerClassifier: Data manager for classification tasks

EmbeddedText: Embedded text

LargeDataSetForText: Abstract class for large data sets containing raw texts

LargeDataSetForTextEmbeddings: Abstract class for large data sets containing text embeddings

Base Models and Transformers

AIFETransformerMaker: R6 class for transformer creation

AIFETrType: Transformer types

aife_transformer_maker: R6 object of the AIFETransformerMaker class

Text Embedding

TEFeatureExtractor: Feature extractor for reducing the number for dimensions of text embeddings.

TextEmbeddingModel: Text embedding model

Classification

TEClassifierProtoNet: Text embedding classifier with a ProtoNet

TEClassifierRegular: Text embedding classifier with a neural net

Auxiliary Functions

Data Management

create_synthetic_units_from_matrix(): Create synthetic units

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

to_categorical_c(): Transforming classes to one-hot encoding

Classification

calc_standard_classification_measures(): Calculate standard classification measures

get_coder_metrics(): Calculate reliability measures based on content analysis

Performance Measures

cohens_kappa(): Calculate Cohen's Kappa

fleiss_kappa(): Calculate Fleiss' Kappa

kendalls_w(): Calculate Kendall's coefficient of concordance w

kripp_alpha(): Calculate Krippendorff's Alpha

For developers

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

.AIFEDebertaTransformer: Child R6 class for creation and training of DeBERTa-V2 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

Large Data Sets

LargeDataSetBase: Abstract base class for large data sets

Classifiers

AIFEBaseModel: Base class for models using neural nets

Utils

auto_n_cores(): Number of cores for multiple tasks

clean_pytorch_log_transformers(): Clean pytorch log of transformers

create_dir(): Create directory if not exists

generate_id(): Generate ID suffix for objects

get_file_extension(): Get file extension

is.null_or_na(): Check if NULL or NA

output_message(): Print message

print_message(): Print message (message())

run_py_file(): Run python file

AI for Education Studio

long_load_target_data(): Load target data for long running tasks