bugfix in PACC
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@ -207,7 +207,7 @@ class ACC(AggregativeQuantifier):
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class_count = data.counts()
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# fit the learner on all data
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self.learner.fit(*data.Xy)
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self.learner, _ = training_helper(self.learner, data, fit_learner, val_split=None)
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else:
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self.learner, val_data = training_helper(self.learner, data, fit_learner, val_split=val_split)
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@ -294,7 +294,7 @@ class PACC(AggregativeProbabilisticQuantifier):
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y_ = np.vstack(y_)
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# fit the learner on all data
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self.learner.fit(*data.Xy)
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self.learner, _ = training_helper(self.learner, data, fit_learner, ensure_probabilistic=True, val_split=None)
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else:
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self.learner, val_data = training_helper(
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@ -12,7 +12,8 @@ plt.rcParams['figure.dpi'] = 200
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plt.rcParams['font.size'] = 16
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def binary_diagonal(method_names, true_prevs, estim_prevs, pos_class=1, title=None, show_std=True, legend=True, savepath=None):
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def binary_diagonal(method_names, true_prevs, estim_prevs, pos_class=1, title=None, show_std=True, legend=True,
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train_prev=None, savepath=None):
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fig, ax = plt.subplots()
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ax.set_aspect('equal')
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ax.grid()
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@ -33,6 +34,10 @@ def binary_diagonal(method_names, true_prevs, estim_prevs, pos_class=1, title=No
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if show_std:
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ax.fill_between(x_ticks, y_ave - y_std, y_ave + y_std, alpha=0.25)
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if train_prev is not None:
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train_prev = train_prev[pos_class]
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ax.scatter(train_prev, train_prev, c='c', label='tr-prev', linewidth=2, edgecolor='k', s=100, zorder=3)
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ax.set(xlabel='true prevalence', ylabel='estimated prevalence', title=title)
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ax.set_ylim(0, 1)
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ax.set_xlim(0, 1)
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