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WordPlotter Example#
This example shows how to use the WordPlotter
class
to generate a word cloud to study the learner’s knowledge.
In this example, we use the KnowledgeClassifier
to build
a representation of the learner’s knowledge. You could also use
other classifiers like NoveltyClassifier
.

from truelearn import learning, datasets
from truelearn.utils import visualisations
# use a custom knowledge component
# you can always use your knowledge component here
# as soon as it follows the protocol of history aware knowledge component
data, _, _ = datasets.load_peek_dataset(test_limit=0, verbose=False)
# select a learner from data
_, learning_events = data[12]
classifier = learning.KnowledgeClassifier()
for event, label in learning_events:
classifier.fit(event, label)
plotter = visualisations.WordPlotter()
plotter.plot(classifier.get_learner_model().knowledge)
plotter.show()
Total running time of the script: (0 minutes 9.467 seconds)