def get_result(self, point):
if not self.ready_model:
self.eval()
distance_list = []
index = 0
while index < len(self.point_list):
w_distance = euclidean_distance(self.point_list[index], point)+\
euclidean_distance(self.point_list[index], self.class_table[self.class_list[index]])
distance_list.append({
'class': self.class_list[index],
'distance': w_distance
})
index+=1
distance_list.sort(key = lambda x: x['distance'])
fav = distance_list[:self.k]
fav_class = {}
for item in fav:
fav_class.setdefault(item['class'], 0)
fav_class[item['class']]+=1
fav_class_items = fav_class.items()
# Будем отдавать наиболее часто встречаюшегося соседа
fav_class_items.sort(key = lambda x:x[1])
return fav_class_items[-1][0]
def get_result(self, point):
if not self.ready_model:
self.eval()
distance_list = []
index = 0
while index < len(self.point_list):
w_distance = euclidean_distance(self.point_list[index], point)+\
euclidean_distance(self.point_list[index], self.class_table[self.class_list[index]])
distance_list.append({
'class': self.class_list[index],
'distance': w_distance
})
index += 1
distance_list.sort(key=lambda x: x['distance'])
fav = distance_list[:self.k]
fav_class = {}
for item in fav:
fav_class.setdefault(item['class'], 0)
fav_class[item['class']] += 1
fav_class_items = fav_class.items()
# Будем отдавать наиболее часто встречаюшегося соседа
fav_class_items.sort(key=lambda x: x[1])
return fav_class_items[-1][0]
def get_result(self, point):
distance_list = {}
if not self.ready_model:
self.eval()
for (_class, centre) in self.class_table.items():
distance_list[_class] = euclidean_distance(centre, point)
fav_class_items = distance_list.items()
# Будем отдавать класс с наиболее близким центром
fav_class_items.sort(key = lambda x:x[1])
return fav_class_items[0][0]
def get_result(self, point):
distance_list = {}
if not self.ready_model:
self.eval()
for (_class, centre) in self.class_table.items():
distance_list[_class] = euclidean_distance(centre, point)
fav_class_items = distance_list.items()
# Будем отдавать класс с наиболее близким центром
fav_class_items.sort(key=lambda x: x[1])
return fav_class_items[0][0]
