#!/usr/bin/env python
from __future__ import division
from __future__ import absolute_import
import numpy
from .Algorithm import Algorithm
import logging
logger = logging.getLogger(__name__)
class Weighted_Sum(Algorithm):
"""weighted sum (default: mean)"""
[docs] def __init__(self, weights=None, **kwargs):
super(Weighted_Sum, self).__init__(
classifier=self,
**kwargs)
self.weights = weights
self.str['weights'] = weights
[docs] def fit(self, X, y):
pass
[docs] def decision_function(self, scores):
if self.weights is None:
return numpy.mean(scores, axis=1)
else:
return numpy.sum(scores * self.weights, axis=1)