def __init__(self, targets=None, dtype=np.int64):
super().__init__()
if targets is not None:
self.n_targets = len(targets)
else:
self.n_targets = 0
self.confusion_matrix = ConfusionMatrix(self.n_targets, dtype)
self.last_true_label = None
self.last_prediction = None
self.last_sample = None
self.sample_count = 0
self.majority_classifier = 0
self.correct_no_change = 0
self.targets = targets
def __init__(self, targets=None, dtype=np.int64, window_size=200):
super().__init__()
if targets is not None:
self.n_targets = len(targets)
else:
self.n_targets = 0
self.confusion_matrix = ConfusionMatrix(self.n_targets, dtype)
self.last_class = None
self.targets = targets
self.window_size = window_size
self.true_labels = FastBuffer(window_size)
self.predictions = FastBuffer(window_size)
self.temp = 0
self.last_prediction = None
self.last_true_label = None
self.last_sample = None
self.majority_classifier = 0
self.correct_no_change = 0
self.majority_classifier_correction = FastBuffer(window_size)
self.correct_no_change_correction = FastBuffer(window_size)