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In data analysis, anomaly detection (also referred to as outlier detection and sometimes as novelty detection) is generally understood to be the identification of rare items, events or observations which deviate significantly from the majority of the data and do not conform to a well defined notion of normal behavior. [1]
Scale AI is an American data annotation company in San Francisco, California. It provides labeled data used to train AI applications. It provides labeled data used to train AI applications. Background
In anomaly detection, the local outlier factor (LOF) is an algorithm proposed by Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng and Jörg Sander in 2000 for finding anomalous data points by measuring the local deviation of a given data point with respect to its neighbours.
The biggest outlier on this list, by far, is MicroStrategy -- which has gained nearly 3,000% since January 2018. The primary reason for MicroStrategy's surge is due to the company's adoption of ...
AI stocks and the broader tech sector plunged on the news, reeling from the potential implications for the industry: ... Alphabet was the outlier, selling for a discount at 27 times earnings. It's ...
A cheaper, competitive AI model from Chinese artificial intelligence company DeepSeek sparked a sell-off in the S&P 500 and ... is expected to be less of an outlier."