Function alp_uncertainty

examples/runtime_comparison.py:163–173

(X, y, n_queries)

@timeit()
def alp_uncertainty(X, y, n_queries):
    X_labeled, y_labeled = X[[0, 50, 100]], y[[0, 50, 100]]
    estimator = LogisticRegression(solver='liblinear', n_jobs=1, multi_class='ovr')
    estimator.fit(X_labeled, y_labeled)
    learner = ActiveLearnerALP(strategy='least_confident')

    for _ in range(n_queries):
        query_idx = learner.rank(estimator, X, num_queries=1)
        X_labeled = np.concatenate((X_labeled, X[query_idx]), axis=0)
        y_labeled = np.concatenate((y_labeled, y[query_idx]), axis=0)
        estimator.fit(X_labeled, y_labeled)


@timeit()