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What is text clustering? Text clustering is to transform the original natural language text information into mathematical information, which is displayed in the form of high-dimensional spatial points. By calculating the distance between those points, those points are clustered into a cluster, and the center of the cluster is called the cluster ...

(this article is part of TensorFlow Object_detection API framework, which is used to train your own model anchor box.) Many object detection models use anchor boxes as the area sampling strategy, so during training, the model learns to match one of several predefined anchor boxes with the ground live boundary box. In order to optimize the accur ...

1, Basic knowledge of cluster analysis Cluster analysis is also called clustering. It is different from classification. The target variables of classification are known. Each sample has a class label, and the target variables of clustering are unknown in advance. The sample categories of clustering are not defined in advance. Clustering is div ...

k-means algorithm Partition based method Given a data set D with N data objects and the number of clusters to be generated K (k < n), in the partition method D, the objects are allocated to K groups, and each group represents a cluster. Then an objective function is used to evaluate the partition quality, so that the objects in the cluster ...

catalogue Unsupervised learning 1 -- clustering What is unsupervised learning? What are the applications of clustering?   K-means algorithm Language expression steps   Pseudo code represents the process of k-means   It is often used to solve the problem of poorly separated clusters Optimization objectives   Random i ...

summary KMeans is an unsupervised learning method. He is a classification algorithm. It is used to explore the original data and classify the samples with the same attributes in the original data. This article only talks about the simple use of KMeans. For the content about the evaluation results, see my next article. Several concepts in ...