API Reference
Data and datasets
Read data
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Load data from file, URL, or plugin. |
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Data object to the dataset with texts, labels, DOIs etc. |
Statistics
Return the average length of the abstracts. |
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Number of duplicates. |
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Return the number of irrelevant records. |
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Return the number of keywords. |
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Return the number of records with missing abstracts. |
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Return the number of records with missing titles. |
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Return the number of records. |
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Return the number of relevant records. |
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Return the number of unlabeled records. |
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Return the average length of the titles. |
Datasets
Available datasets
Datasets available in the benchmark platform. |
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Datasets used in the paper Van de Schoot et al. 2020. |
Dataset managers
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Reviewer
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Base class for Systematic Review. |
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ASReview Simulation mode class. |
Models
Base class
Abstract class for any kind of model. |
asreview.models.balance
Classes
Abstract class for balance strategies. |
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Simple (no balancing) balance strategy. |
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Double balance strategy. |
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Triple balance strategy. |
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Undersampling balance strategy. |
Functions
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Get an instance of a balance model from a string. |
Get class of balance model from string. |
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List available balancing strategy classes. |
asreview.models.classifiers
Classes
Base model, abstract class to be implemented by derived ones. |
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Naive Bayes classifier. |
Random forest classifier. |
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Support vector machine classifier. |
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Logistic regression classifier. |
LSTM-base classifier. |
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LSTM-pool classifier. |
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Fully connected neural network (2 hidden layers) classifier. |
Functions
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Get an instance of a model from a string. |
Get class of model from string. |
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List available classifier classes. |
asreview.models.feature_extraction
Classes
Base class for feature extraction methods. |
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TF-IDF feature extraction technique. |
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Doc2Vec feature extraction technique. |
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Embedding IDF feature extraction technique. |
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Embedding LSTM feature extraction technique. |
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Sentence BERT feature extraction technique. |
Functions
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Get an instance of a feature extraction model from a string. |
Get class of feature extraction from string. |
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List available feature extraction method classes. |
asreview.models.query
Classes
Abstract class for query strategies. |
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Maximum query strategy. |
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Mixed query strategy. |
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Mixed (95% Maximum and 5% Random) query strategy. |
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Mixed (95% Maximum and 5% Uncertainty) query strategy. |
Uncertainty query strategy. |
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Random query strategy. |
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Clustering query strategy. |
Functions
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Get an instance of the query strategy. |
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Get class of query strategy from its name. |
List available query strategy classes. |
Projects and States
Load, interact, and extract information from project files and states (the “diary” of the review).
ASReviewProject
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Project class for ASReview project files. |
State
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Initialize a state class instance from a project folder. |
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Class for storing the review state. |
Utils
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Get the project directory. |
List the projects in the asreview path |
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Check if a project file is of a ASReview version 0 project. |
Readers and writers
This module contains the input and output functionality. You can install them as extensions.
List available dataset reader classes. |
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List available dataset writer classes. |
CVS file reader. |
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CSV file writer. |
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Excel file reader. |
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Excel file writer. |
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A single record from a paper in a systematic review. |
RIS file reader. |
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RIS file writer. |
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TSV file writer. |
Misc
Classes
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Object to store the configuration of a review session. |
Functions
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Find a record using keywords. |
Get the location where projects are stored. |
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Return the path of the ASR data dir. |
Entry points
Entry points for ASReview LAB.
Base class for defining entry points. |
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Entry point to list available algorithms in ASReview LAB. |
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Entry point to start the ASReview LAB webapp. |
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Entry point for simulation with ASReview LAB. |
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Entry point to inspect ASReview LAB review progress. |