官术网_书友最值得收藏!

Summary

In this chapter, we have explored what clustering is and why it is important in a variety of data challenges. Building upon this foundation of clustering knowledge, you implemented k-means, which is one of the simplest, yet most popular, methods of unsupervised learning. If you have reached this summary and can repeat what k-means does step by step to a friend, then you're ready to move on to more complex forms of clustering.

From here, we will be moving on to hierarchical clustering, which, in one configuration, reuses the centroid learning approach that we used in k-means. We will build upon this approach by outlining additional clustering methodologies and approaches in the next chapter.

主站蜘蛛池模板: 亚东县| 延庆县| 青阳县| 册亨县| 札达县| 蚌埠市| 温州市| 铜陵市| 延长县| 香港 | 衡南县| 江油市| 大渡口区| 虎林市| 广东省| 宁强县| 图们市| 昭通市| 岳西县| 梨树县| 股票| 鄂托克旗| 蒙自县| 井研县| 韶关市| 滦南县| 名山县| 旬邑县| 宁晋县| 琼海市| 文山县| 和硕县| 河间市| 河曲县| 长海县| 枞阳县| 台南市| 砚山县| 达州市| 蓝田县| 基隆市|