def fit(self, X, y):
self.reset_counts()
X = safe_get_values(X)
# keeping this variable local because instance method objects
# can't e pickled
key_factory = self._get_key_factory(X)
for row, value in izip(X, y):
hit_count = 1 if value == self.target_value else 0
self.grand_total += 1
self.all_hits += hit_count
key = key_factory(row)
if not check_any_null(key):
self.total[key] += 1
self.hits[key] += hit_count
def fit(self, X, y):
self.reset_counts()
X = safe_get_values(X)
# keeping this variable local because instance method objects
# can't e pickled
key_factory = self._get_key_factory(X)
for row, value in izip(X, y):
hit_count = 1 if value == self.target_value else 0
self.grand_total += 1
self.all_hits += hit_count
key = key_factory(row)
if not check_any_null(key):
self.total[key] += 1
self.hits[key] += hit_count
def fit(self, X, y=None):
self._offset = 0
minval, maxval = None, None
for x in X:
if check_any_null(x):
continue
if minval is None:
minval = x
maxval = x
elif x < minval:
minval = x
elif x > maxval:
maxval = x
if self.has_log_bins:
if minval <= 0:
self._offset = 1 - minval
minval += self._offset
maxval += self._offset
self.bin_edges = np.logspace(np.log10(minval), np.log10(maxval),
self.nbins)
else:
self.bin_edges = np.linspace(minval, maxval, self.nbins)
def fit(self, X, y=None):
self._offset = 0
minval, maxval = None, None
for x in X:
if check_any_null(x):
continue
if minval is None:
minval = x
maxval = x
elif x < minval:
minval = x
elif x > maxval:
maxval = x
if self.has_log_bins:
if minval <= 0:
self._offset = 1 - minval
minval += self._offset
maxval += self._offset
self.bin_edges = np.logspace(np.log10(minval),
np.log10(maxval),
self.nbins)
else:
self.bin_edges = np.linspace(minval, maxval, self.nbins)
