计算Pandas数据框中两行之间LDA分布之间的距离

import pandas as pd
import numpy as np
from scipy.spatial.distance import euclidean

# 导入数据
data = pd.read_csv("data.csv")

# 数据预处理和向量化

# 应用LDA模型
# lda_model = ...  # LDA模型的创建和训练

# 获取每行数据的LDA分布
lda_distributions = lda_model.transform(vectorized_data)

# 获取两行数据的索引
row1_index = 0  # 第一行数据的索引
row2_index = 1  # 第二行数据的索引

# 获取两行数据的LDA分布
lda_distribution_row1 = lda_distributions[row1_index]
lda_distribution_row2 = lda_distributions[row2_index]

# 计算距离
distance = euclidean(lda_distribution_row1, lda_distribution_row2)

print("行{}和行{}之间的LDA分布距离为{}".format(row1_index, row2_index, distance))