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1 day ago · Alibi Detect is a Python library for detecting outliers, adversarial data, and drift. The package aims to include detectors for tabular data, text, images, and time series that can be used both online and offline. For drift detection, both TensorFlow and PyTorch backends are supported. In fact, Alibi Detect supports a variety of outlier ...
5 days ago · Outlier detection is not a one-size-fits-all process. The effectiveness of identifying outliers largely depends on the context and domain of the dataset you’re working with. Here’s how domain knowledge and contextual factors can influence outlier detection.
5 days ago · Detection of multivariate outliers is crucial in statistical studies. On the other hand, the statistical applications without identifying possible outliers may present incorrect results. This study proposes a new technique for detecting multivariate outliers based on cluster analysis.
3 days ago · We propose a novel distribution-aware anomaly detection mechanism, BoBa, to address this problem. In order to differentiate outliers arising from data variety versus backdoor attack, we propose to break down the problem into two steps: clustering clients utilizing their data distribution followed by a voting-based detection.
4 days ago · BARO leverages the Multivariate Bayesian Online Change Point Detection technique to model the dependency within multivariate time-series metrics data, enabling it to detect anomalies more accurately. BARO also incorporates a novel nonparametric statistical hypothesis testing technique for robustly identifying root causes, which is less sensitive to the accuracy of anomaly detection compared to existing works.
5 days ago · Traditional outlier detection methods do not explicitly minimise intra-class distances, but they enhance separability using techniques such as Gaussian Radial Basis Function (RBF) kernels . This study aims to minimise intra-class distances for all latent layer embeddings, a distinction from typical outlier detection methods.
5 days ago · How are box plots used? Box plots help you see the center and spread of data. You can also use them as a visual tool to check for normality or to identify points that may be outliers. Is a box plot the same as a box-and-whisker plot? Yes. Box plots may also be called outlier box plots or quantile box plots.
