[[["わかりやすい","easyToUnderstand","thumb-up"],["問題の解決に役立った","solvedMyProblem","thumb-up"],["その他","otherUp","thumb-up"]],[["必要な情報がない","missingTheInformationINeed","thumb-down"],["複雑すぎる / 手順が多すぎる","tooComplicatedTooManySteps","thumb-down"],["最新ではない","outOfDate","thumb-down"],["翻訳に関する問題","translationIssue","thumb-down"],["サンプル / コードに問題がある","samplesCodeIssue","thumb-down"],["その他","otherDown","thumb-down"]],["最終更新日 2024-07-22 UTC。"],[[["The k-means clustering algorithm groups data points into clusters by minimizing the distance between each point and its cluster's centroid."],["K-means is efficient, scaling as O(nk), making it suitable for large datasets in machine learning, unlike hierarchical clustering methods."],["The algorithm iteratively refines clusters by recalculating centroids and reassigning points until convergence or a stopping criteria is met."],["Due to random initialization, k-means can produce varying results; running it multiple times and selecting the best outcome based on quality metrics is recommended."],["K-means assumes data is composed of circular distributions, which may not be accurate for all real-world data containing outliers or density-based clusters."]]],[]]