agglomerative

agglomerative的音标为[ˌægləˈmɔːrətɪv]：adj. 聚类的；合并的。

基本翻译为“聚类的”，表示将事物或想法聚集在一起。速记技巧可以是将每个音节分开记，注意重读和轻读的区别，这样可以更快速地记住这个单词。同时，可以结合具体的语境来理解和记忆这个单词，例如在讨论分类、分组、合并等主题时，可以联想到这个单词。

Agglomerative这个词的词源可以追溯到拉丁语和希腊语，意为“聚集的，集合的”。它的变化形式包括agglomerate（聚集，凝结），agglomeration（聚集，凝结物），agglomerator（凝结器）。

相关单词：

1. Clustering：这个词与agglomerative有相似的含义，意为“聚类的，集群的”。例如，在数据科学中，我们可能会使用clustering算法来对数据进行分组或聚类。

2. Convergent：这个词表示向一点聚集或集中，与agglomerative有相似的含义。例如，在社交网络中，用户可能会向共同兴趣的群体或话题聚集。

3. Aggregated：这个词表示将事物聚集在一起，与agglomerative的含义相符。例如，在数据分析中，我们可能会将数据聚合在一起以进行更深入的分析。

以上这些单词都与agglomerative有相似的含义，它们在英语中都有广泛的用途，并且在不同的语境中有着不同的含义和用法。

agglomerative短语：

1. agglomerative clustering 凝聚型聚类

2. agglomerative hierarchy 凝聚层次

3. agglomerative method 凝聚法

4. agglomerative method of classification 凝聚分类法

5. agglomerative clustering analysis 凝聚型聚类分析

6. agglomerative hierarchical clustering 凝聚型分层聚类

7. agglomerative hierarchical methods 凝聚型分层法

双语例句：

1. We used agglomerative clustering to analyze the data and found that there were two main groups of customers. 我们用凝聚型聚类法分析了数据，发现客户主要分为两类。

2. The data was then subjected to agglomerative hierarchical clustering, which produced a dendrogram showing the relationships between the different samples. 然后对数据进行凝聚型分层聚类分析，生成了显示不同样本之间关系的树状图。

3. Agglomerative clustering is a type of unsupervised machine learning algorithm that groups similar items together based on their similarity scores. 凝聚型聚类是一种无监督的机器学习算法，它将相似项根据相似度得分聚合成组。

4. The results of agglomerative hierarchical clustering showed that the samples were divided into two main groups, indicating that there were significant differences between them. 凝聚型分层聚类的结果表明，样品被分为两个主要组，表明它们之间存在显著差异。

5. Agglomerative clustering is a type of clustering algorithm that starts with no groups and then gradually forms clusters by merging similar ones. 凝聚型聚类是一种从无组开始逐渐形成相似组的聚类算法。

6. The data was then analyzed using agglomerative hierarchical clustering, which produced a dendrogram showing the relationships between the different items. 然后对数据进行了凝聚型分层聚类分析，生成了显示不同项目之间关系的树状图。

7. The dendrogram generated by the agglomerative hierarchical clustering method provided a visual representation of the relationships between the items in the dataset. 通过凝聚型分层聚类方法生成的树状图提供了数据集中项目之间关系的可视化表示。

英文小作文：

Agglomerative clustering is a type of unsupervised machine learning algorithm that groups similar items together based on their similarity scores. It is commonly used in data analysis and classification tasks to identify patterns and trends in data sets.

One application of agglomerative clustering is in market research, where companies can use it to analyze customer data and identify groups of customers with similar buying patterns and preferences. This helps companies target their marketing campaigns more effectively and increase sales.

Another application of agglomerative clustering is in bioinformatics, where it can be used to analyze large amounts of genetic data and identify patterns in gene expression and disease progression. This can help researchers identify new drug targets and develop more effective treatments for diseases.

Agglomerative clustering is a powerful tool that can be used to analyze any type of data set and identify patterns and trends that may be hidden within the data. It is a useful technique for data analysts and machine learning experts who are looking for ways to improve their analysis and decision-making processes.