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pd.DataFrame(cosine_similarity

时间: 2023-09-22 17:10:18 浏览: 123

pyspark.sql.DataFrame与pandas.DataFrame之间的相互转换实例

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代码如下，步骤流程在代码注释中可见： # -*- coding: utf-8 -*- import pandas as pd from pyspark.sql import SparkSession from pyspark.sql import SQLContext from pyspark import SparkContext #初始化数据 #初始化pandas DataFrame df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], index=['row1', 'row2'], columns=['c1', 'c2', 'c3']) #打印数据 pri

cosine_similarity是sklearn.metrics.pairwise模块中的一个函数，用于计算两个向量之间的余弦相似度。123 #### 引用[.reference_title] - *1* [机器学习-文本数据-文本的相关性矩阵 1.cosing_similarity(用于计算两两特征之间的相关性)](https://blog.csdn.net/weixin_39847437/article/details/110690430)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT0_1"}}] [.reference_item style="max-width: 50%"] - *2* *3* [pandas.DataFrame corrwith（）方法](https://blog.csdn.net/weixin_39990410/article/details/111429993)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT0_1"}}] [.reference_item style="max-width: 50%"] [ .reference_list ]

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