Selected article for: "Embedding algorithm and Stochastic Neighbour Embedding algorithm"

Author: Yujia Xiang; Quan Zou; Lilin Zhao
Title: VPTMdb: a viral post-translational modification database
  • Document date: 2020_4_2
  • ID: kl99afiu_66
    Snippet: To understand the effective of our 68-dimensional features, the Tdistributed Stochastic Neighbour Embedding (t-SNE) algorithm was used to visualize the positive and negative samples. A clear distinction was observed between the positive and negative samples, implying that our features selection results are effective (Fig. 3B) ......
    Document: To understand the effective of our 68-dimensional features, the Tdistributed Stochastic Neighbour Embedding (t-SNE) algorithm was used to visualize the positive and negative samples. A clear distinction was observed between the positive and negative samples, implying that our features selection results are effective (Fig. 3B) .

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