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请输入英文单字，中文词皆可：

conquerable    
a. 可征服的,可打胜的,可击破的

可征服的,可打胜的,可击破的

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  • When to use hierarchical clustering - Crunching the Data
    In general, you should use hierarchical clustering for datasets that do not have a clear outcome variable to predict Hierarchical clustering can help you detect patterns in your data even when you do not have a designated outcome variable
  • Hierarchical Clustering: Applications, Advantages, and . . .
    Hierarchical clustering is an unsupervised machine-learning algorithm used to group data points into clusters In this article, we will discuss the basics of hierarchical clustering, its advantages, disadvantages, and applications in real-life situations What is Hierarchical Clustering?
  • Clustering Text Data: A Practical Guide - Flare Compare
    Clustering text data is an essential task in Natural Language Processing (NLP), and there are various methods to achieve it In this practical guide, we compared K-Means clustering, Hierarchical clustering, and Density-based clustering to cluster text data
  • When to Use Hierarchical Clustering: A Guide for Data Analysts
    When it comes to clustering, hierarchical clustering is a popular method used in data mining and statistics It is a technique that seeks to build a hierarchy of clusters by iteratively grouping or separating data points
  • Comprehensive Guide to Hierarchical Cluster Analysis in Data . . .
    Hierarchical clustering can be broadly categorized into agglomerative and divisive methods, each with its own approach and applications Hierarchical cluster analysis involves creating a tree-like structure called a dendrogram, which visually represents the nested clusters
  • Incremental hierarchical text clustering methods: a review
    The technique presented, referred to as LUPI-Based Incremental Hierarchical Clustering (LIHC), uses the subset containing this privileged information and applies various clustering algorithms to it; consensus clustering is used to generate the initial partitioning data model





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