Semantic Embedding for Medical Providers and Fraud Detection
论文传送门 作者 佛罗里达大西洋大学 Justin M. Johnson Taghi M. Khoshgoftaar 摘要 一个医疗提供者的专业是一个重要的预测指标，可以用机器学习算法检测出欺诈提供者。然而，当特殊变量编码使用 one-hot 表示，模型接受稀疏和信息量不大的特征向量。我们探讨了三种技术，用于使用密集的语义嵌入表示医疗提供者类型，从而捕获专业相似性。前两种方法(GloVe和Med-
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相关文章
- 1. RCNN：Rich feature hierarchies for accurate object detection and semantic segmentation
- 2. Rich feature hierarchies for accurate object detection and semantic segmentation
- 3. Object Detection Network———Rcnn（Rich feature hierarchies for accurate oject detection and semantic ）
- 4. [Angular] Providers and useFactory
- 5. 论文阅读：Associative Embedding: End-to-End Learning for Joint Detection and Grouping
- 6. Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
- 7. Medicare Fraud Detection using Machine Learning
- 8. SemEval2019Task3_ERC | (2) Attentive Conversation Modeling for Emotion Detection and Classification
- 9. 目标检测--Rich feature hierarchies for accurate object detection and semantic segmentation(CVPR 2014)
- 10. RCNN学习笔记(1):Rich feature hierarchies for accurate object detection and semantic segmentation