পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| কে-মিনস ক্লাস্টারিং× | অনলাইন লার্নিং× | |
|---|---|---|
| ক্ষেত্র | যন্ত্র শিখন | যন্ত্র শিখন |
| পরিবার | Machine learning | Machine learning |
| উদ্ভবের বছর≠ | 1967 (formalized 1982) | 1958–2000s |
| প্রবর্তক≠ | MacQueen, J. B.; Lloyd, S. P. | Rosenblatt, F.; Littlestone, N.; Shalev-Shwartz, S. (key contributors) |
| ধরন≠ | Partitional clustering | Learning paradigm (sequential model update) |
| মৌলিক উৎস≠ | Lloyd, S. P. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129–137. DOI ↗ | Shalev-Shwartz, S. (2011). Online Learning and Online Convex Optimization. Foundations and Trends in Machine Learning, 4(2), 107–194. DOI ↗ |
| অপর নাম | k-means clustering, Lloyd's algorithm, k-means partitioning, hard k-means | incremental learning, sequential learning, streaming learning, online machine learning |
| সম্পর্কিত≠ | 4 | 6 |
| সারসংক্ষেপ≠ | K-means is a classic unsupervised partitional clustering algorithm that divides a dataset into K non-overlapping groups by iteratively assigning each observation to its nearest centroid and updating centroids as the mean of their assigned points. It is one of the most widely used exploratory tools in machine learning and data analysis. | Online learning is a machine learning paradigm in which a model is updated incrementally as each new data point arrives, rather than being trained once on a fixed dataset. It is essential when data streams continuously, storage is limited, or the underlying distribution shifts over time. Theoretical performance is measured by cumulative regret relative to the best fixed predictor in hindsight. |
| ScholarGateডেটাসেট ↗ |
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