BUC算法用python实现
时间: 2023-11-25 18:51:24 浏览: 33
以下是一个用Python实现BUC算法的示例代码:
```python
def buc(data, min_support):
# 计算整个数据集的度量值
measure = len(data)
# 如果数据集为空,则返回空字典
if measure == 0:
return {}
# 如果数据集只有一个元素,则返回该元素的计数
if measure == 1:
return {data[0]: 1}
# 对数据集进行维度划分
dimensions = []
for i in range(len(data[0])):
dimension = set([d[i] for d in data])
dimensions.append(list(dimension))
# 对每个维度进行属性划分
partitions = []
for i in range(len(dimensions)):
partition = []
for j in range(len(dimensions[i])):
partition.append([d for d in data if d[i] == dimensions[i][j]])
partitions.append(partition)
# 对每个划分进行聚集
result = {}
for i in range(len(partitions)):
for j in range(len(partitions[i])):
count = len(partitions[i][j])
if count >= min_support:
key = tuple([dimensions[i][j]])
if len(key) == 1:
key = key[0]
result[key] = count
sub_result = buc(partitions[i][j], min_support)
for k, v in sub_result.items():
new_key = tuple(sorted(list(key) + list(k)))
if len(new_key) == 1:
new_key = new_key[0]
if new_key in result:
result[new_key] += v
else:
result[new_key] = v
return result
```
该代码实现了BUC算法的主要流程,包括数据集的维度划分、属性划分、聚集和递归调用。其中,min_support参数表示最小支持度,用于判断是否满足冰山条件。该函数返回一个字典,其中键为聚集元组,值为聚集计数。