def __init__(self, model, loss, size, p, seed=None):
self.model = model
self.loss = loss
self.p = p
self.size = size
self.buffer = utils.SortedWindow(self.size)
self.seed = seed
self._rng = random.Random(seed)
def __init__(self, q, window_size):
self.window = utils.SortedWindow(size=window_size)
self.q = q
idx = self.q * (self.window.size - 1)
self._lower = int(math.floor(idx))
self._higher = self._lower + 1
if self._higher > self.window.size - 1:
self._higher = self.window.size - 1
self._frac = idx - self._lower
def __init__(self, model, loss, size, p, seed=None):
self.model = model
self.loss = loss
self.pred_func = model.predict_one
if isinstance(model, base.Classifier):
self.pred_func = model.predict_proba_one
if not model._multiclass:
self.pred_func = lambda x: model.predict_proba_one(x)[True]
self.p = p
self.size = size
self.buffer = utils.SortedWindow(self.size)
self.seed = seed
self._rng = random.Random(seed)
def __init__(self, window_size: int):
self.window = utils.SortedWindow(size=window_size)