Outlier Detection Using Vector Cosine Similarity by Adding a Dimension
We propose a new outlier detection method for multi-dimensional data. The method detects outliers based on vector cosine similarity, using a new dataset constructed by adding a dimension with zero values to the original data. When a point in the new dataset is selected as the measured point, an observation point is created as the origin, differing only in the new dimension by having a non-zero value compared to the measured point. Vectors are then formed from the observation point to the measured point and to other points in the dataset. By comparing the cosine similarities of these vectors, abnormal data can be identified. An optimized implementation (MDOD) is available on PyPI: https://pypi.org/project/mdod/.
Code (0)
등록된 구현이 없습니다.
Tasks
Outlier DetectionSimilar Papers 제목 키워드 기반
A Rank-Based Similarity Metric for Word Embeddings
Word Embeddings have recently imposed themselves as a standard for representing word meaning in NLP. Semantic similarity between word pairs has become the most common evaluation benchmark for these representations, with …
ClusteringOutlier DetectionSemantic SimilaritySemantic Textual Similarity+1Similarity-based Outlier Detection for Noisy Object Re-Identification Using Beta Mixtures
Object re-identification (Re-ID) methods are highly sensitive to label noise, which typically leads to significant performance degradation. We address this challenge by reframing Re-ID as a supervised image similarity ta…
Outlier DetectionPlagiarism Detection on Electronic Text based Assignments using Vector Space Model (ICIAfS14)
Plagiarism is known as illegal use of others' part of work or whole work as one's own in any field such as art, poetry, literature, cinema, research and other creative forms of study. Plagiarism is one of the important i…
Enhancement to Training of Bidirectional GAN : An Approach to Demystify Tax Fraud
Outlier detection is a challenging activity. Several machine learning techniques are proposed in the literature for outlier detection. In this article, we propose a new training approach for bidirectional GAN (BiGAN) to …
Outlier DetectionSteering Awareness: Detecting Activation Steering from Within
Activation steering -- adding a vector to a model's residual stream to modify its behavior -- is widely used in safety evaluations as if the model cannot detect the intervention. We test this assumption, introducing stee…