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Exercise

Implementing an active learning pipeline

In this exercise, you'll set up an active learner using a logistic regression model and an uncertainty sampling strategy.

The dataset has been loaded with X_labeled for labeled training data, X_unlabeled for unlabeled training data, and y_labeled for labels.

The required libraries have been imported: ActiveLearner from modAL.models, uncertainty_sampling from modAL.uncertainty and LogisticRegression from sklearn.linear_model.

Instructions

100 XP
  • Initialize an ActiveLearner object.
  • Use LogisticRegression as the estimator.
  • Use uncertainty sampling as the query strategy.
  • Initialize the learner with labeled training data.