API Reference#
Shown is the class and function hierarchy of TrueLearn.
For a more detailed description of the decisions made during implementation, please refer to the Design Considerations section.
truelearn.base
: Contains the base classes for the library#
Base Classes#
The base class of all the classifiers in TrueLearn. |
truelearn.datasets
: Contains utilities for using datasets#
The truelearn.datasets module contains utilities to load datasets, such as the PEEK dataset.
Classes#
A class that defines an implicit interface to the generator of the knowledge component. |
Functions#
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Download and Parse PEEKDataset. |
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Download and Load the raw PEEKDataset. |
truelearn.learning
: Contains the classifiers for learning#
The truelearn.learning module implements the classifiers in TrueLearn paper.
Classes#
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A meta-classifier that combines KnowledgeClassifier and InterestClassifier. |
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A classifier that models the learner's interest and makes prediction based on the interest. |
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A classifier that models the learner's knowledge and makes prediction based on the knowledge. |
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A classifier that models the learner's knowledge and makes prediction based on the knowledge. |
A Classifier that always makes a positive prediction. |
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A classifier that makes predictions based on whether the learner has engaged with the last learnable unit. |
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A classifier that predicts based on the number of learner's engagement and non-engagement. |
truelearn.models
: Contains the representations used for learning#
The truelearn.models module implements the knowledge, learner and event models.
Classes#
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An interface defines a knowledge component of a learnable unit. |
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A class that models a learning event in TrueLearn algorithm. |
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The model of a learner. |
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Store the weights used in meta training. |
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A concrete class that implements BaseKnowledgeComponent. |
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A knowledge component that keeps a history about how it was updated. |
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The representation of the learner's knowledge. |
truelearn.preprocessing
: Contains preprocessing functions and classes#
The truelearn.preprocessing module implements the initial tasks required to use the classifiers.
Classes#
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A client that makes requests to the Wikifier API. |
Functions#
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Calculate the mean of an iterable of values. |
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Calculate the sample standard deviation of an iterable of values. |
Calculate the population standard deviation of an iterable of values. |
truelearn.utils.metrics
: Contains functions to generate metrics#
The truelearn.utils.metrics implements the commonly-used metrics in TrueLearn.
Functions#
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Get the precision score of the prediction. |
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Get the recall score of the prediction. |
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Get the accuracy score of the prediction. |
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Get the f1 score of the prediction. |
truelearn.utils.visualisations
: Contains plotting functions and classes#
truelearn.utils.visualisations provides utilities for creating visualisations.
The module provides Plotter classes that take the learner’s knowledge as input and produce various different charts.
Classes#
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Line plotter. |
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Pie plotter. |
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Rose pie plotter. |
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Bar plotter. |
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Dot plotter. |
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Bubble plotter. |
Word cloud plotter. |
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Radar plotter. |
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Treemap plotter. |