Sentence examples for cluster learning from inspiring English sources
And compared with the cluster learning algorithm, the correct rate of recognition increased by 5% when training samples fusion method was adopted.
The experiment demonstrated that HLSI can successfully cluster learning styles into three or four combinations based on learning performance, which suggests that the data mining technique can successfully explore multiple learning styles in problem-solving abilities.
To date, most algorithms generally treat clustering learning and classification learning in a sequential or two-step manner, i.e., first execute clustering learning to explore structures in data, and then perform classification learning on top of the obtained structural information.
To measure the unique features of the proposed method, the k-means clustering learning algorithm based on the hybrid RBF-BP network (KMRBF-BP) is also compared with ILRBF-BP on artificial data sets.
Sugano et al. [1] take the cropped eye region as a point in a local manifold model and make gaze estimation by clustering learning samples with similar head poses and constructing their local manifold model.
Properties of Walktrap-GM are compared to those of several other approaches in Table 3, including heuristics for clustering, learning methods and parameter tuning.
Most analyses of the relationship between spatial clustering and the technological learning of firms have emphasised the influence of the former on the latter, and have focused on intra-cluster learning as the driver of innovative performance.
Clustering learning and classification learning are two major tasks in pattern recognition.
The proposed FSLVQ is a batch type of clustering learning network by fusing the batch learning, soft competition and fuzzy membership functions.
In fact, the clustering learning in these algorithms just aids the subsequent classification learning and does not benefit from the latter.
When class information is available, fusing the advantages of both clustering learning and classification learning into a single framework is an important problem worthy of study.
