Package index
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textrpp_install()textrpp_install_virtualenv() - Install text required python packages in conda or virtualenv environment
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textrpp_uninstall() - Uninstall textrpp conda environment
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textrpp_initialize() - Initialize text required python packages
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textDiagnostics() - Run diagnostics for the text package
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textEmbed() - textEmbed() extracts layers and aggregate them to word embeddings, for all character variables in a given dataframe.
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textDimName() - Change dimension names
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textEmbedRawLayers() - Extract layers of hidden states
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textEmbedLayerAggregation() - Aggregate layers
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textEmbedReduce() - Pre-trained dimension reduction (experimental)
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textEmbedStatic() - Apply static word embeddings
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textFineTuneTask() - Task Adapted Pre-Training (EXPERIMENTAL - under development)
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textFineTuneDomain() - Domain Adapted Pre-Training (EXPERIMENTAL - under development)
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textGeneration() - Text generation
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textNER() - Named Entity Recognition. (experimental)
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textSum() - Summarize texts. (experimental)
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textQA() - Question Answering. (experimental)
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textTranslate() - Translation. (experimental)
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textZeroShot() - Zero Shot Classification (Experimental)
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textTrain() - Trains word embeddings
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textTrainLists() - Train lists of word embeddings
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textTrainRegression() - Train word embeddings to a numeric variable.
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textTrainRandomForest() - Trains word embeddings usig random forest
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textTrainN() - Cross-validated accuracies across sample-sizes
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textTrainNPlot() - Plot cross-validated accuracies across sample sizes
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textExamples() - Identify language examples.
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textPredict()textAssess()textClassify() - textPredict, textAssess and textClassify
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textPredictTest() - Significance testing for model prediction performance
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textPredictAll() - Predict from several models, selecting the correct input
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textLBAM() - The LBAM library
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textSimilarity() - Semantic Similarity
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textDistance() - Semantic distance
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textSimilarityMatrix() - Semantic similarity across multiple word embeddings
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textDistanceMatrix() - Semantic distance across multiple word embeddings
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textSimilarityNorm() - Semantic similarity between a text variable and a word norm
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textDistanceNorm() - Semantic distance between a text variable and a word norm
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textProjection() - Supervised Dimension Projection
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textPlot() - Plot words
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textProjectionPlot() - Plot Supervised Dimension Projection
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textCentrality() - Semantic similarity score between single words' and an aggregated word embeddings
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textCentralityPlot() - Plots words from textCentrality()
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textPCA() - textPCA()
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textPCAPlot() - textPCAPlot
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textTopics() - BERTopics
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textTopicsTest() - Wrapper for topicsTest function from the topics package
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textTopicsWordcloud() - Plot word clouds
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textTopicsReduce() - textTopicsReduce (EXPERIMENTAL)
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textTopicsTree() - textTopicsTest (EXPERIMENTAL) to get the hierarchical topic tree
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textModels() - Check downloaded, available models.
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textModelLayers() - Number of layers
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textModelsRemove() - Delete a specified model
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textDescriptives() - Compute descriptive statistics of character variables.
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textClean() - Cleans text from standard personal information
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textTokenize() - Tokenize text-variables
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textTokenizeAndCount() - Tokenize and count
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textDomainCompare() - Compare two language domains
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textFindNonASCII() - Detect non-ASCII characters
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textCleanNonASCII() - Clean non-ASCII characters
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Language_based_assessment_data_8 - Text and numeric data for 10 participants.
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word_embeddings_4 - Word embeddings for 4 text variables for 40 participants
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raw_embeddings_1 - Word embeddings from textEmbedRawLayers function
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Language_based_assessment_data_3_100 - Example text and numeric data.
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DP_projections_HILS_SWLS_100 - Data for plotting a Dot Product Projection Plot.
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centrality_data_harmony - Example data for plotting a Semantic Centrality Plot.
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PC_projections_satisfactionwords_40 - Example data for plotting a Principle Component Projection Plot.
