def disc_gain_rt(self, index, data):
'''
计算一个属性的信息增益
'''
statisc_dict = {}
index_val = self.disc_type[index]
total_info = cal_set_info(data)
for val in index_val:
statisc_dict[val] = {}
for d in data:
if d[-1] in statisc_dict[d[index]]:
statisc_dict[d[index]][d[-1]] += 1
else:
statisc_dict[d[index]][d[-1]] = 1
'''
statisc_dict结构:
{
attr_value1:{yes:num1, no:num2},
...
attr_value2:{yes:num1, no:num2},
}
'''
info_gain, info_measure = cal_gain_ratio(statisc_dict, data)
return -1 if info_measure == -1 else info_gain / info_measure
def disc_gain_rt(self, index, data):
'''
计算一个属性的信息增益
'''
statisc_dict = {}
index_val = self.disc_type[index]
total_info = cal_set_info(data)
for val in index_val:
statisc_dict[val] = {}
for d in data:
if d[-1] in statisc_dict[d[index]]:
statisc_dict[d[index]][d[-1]] += 1
else:
statisc_dict[d[index]][d[-1]] = 1
'''
statisc_dict结构:
{
attr_value1:{yes:num1, no:num2},
...
attr_value2:{yes:num1, no:num2},
}
'''
info_gain, info_measure = cal_gain_ratio(statisc_dict, data)
return -1 if info_measure == -1 else info_gain / info_measure
def num_gain_rt(self, index, data):
'''
连续数值属性计算信息增益，先根据第index列排序，选取标签改变时对应的index列属性值，
作为分界点，分别计算出每个分界点对应的信息增益，返回最大增益及其对应的分界点
'''
ctgs = set()
sorted_data = sorted(data, key=itemgetter(index))
cls = sorted_data[0][-1]
#只选取便签改变时对应的属性值
for d in sorted_data:
if d[-1] != cls:
cls = d[-1]
ctgs.add(d[index])
max_gain, border, gain_ratio = sys.float_info.min, 0.0, -1.0
for ctg in ctgs:
statisc_dict = {}
info_gain = 0.0
'''
结构为
{
'left': {yes: num1, no:num2}
'right': {yes:num1, no:num2}
}
'''
statisc_dict['left'], statisc_dict['right'] = binary_sp(
data, ctg, index)
info_gain, info_measure = cal_gain_ratio(statisc_dict, data)
if info_measure == -1:
continue
if info_gain > max_gain:
max_gain, border, gain_ratio = info_gain, ctg, info_gain / info_measure
return gain_ratio, border
def num_gain_rt(self, index, data):
'''
连续数值属性计算信息增益，先根据第index列排序，选取标签改变时对应的index列属性值，
作为分界点，分别计算出每个分界点对应的信息增益，返回最大增益及其对应的分界点
'''
ctgs = set()
sorted_data = sorted(data, key=itemgetter(index))
cls = sorted_data[0][-1]
#只选取便签改变时对应的属性值
for d in sorted_data:
if d[-1] != cls:
cls = d[-1]
ctgs.add(d[index])
max_gain, border, gain_ratio = sys.float_info.min, 0.0, -1.0
for ctg in ctgs:
statisc_dict = {}
info_gain = 0.0
'''
结构为
{
'left': {yes: num1, no:num2}
'right': {yes:num1, no:num2}
}
'''
statisc_dict['left'], statisc_dict['right'] = binary_sp(data, ctg, index)
info_gain, info_measure = cal_gain_ratio(statisc_dict, data)
if info_measure == -1:
continue
if info_gain > max_gain:
max_gain, border, gain_ratio = info_gain, ctg, info_gain / info_measure
return gain_ratio, border
