Finding the "K most likely outliers", i. e. those K observations whose removal from the data most reduces the sum of squared residuals from a linear model, can require lengthy computation. The ...

Data analytics deals with making observations with various data sets, and trying to make sense of the data. When dealing with very large data sets, automated tools must be used to find patterns and ...

AVGO designs, develops, and supplies semiconductors and infrastructure software solutions, proving to be a key driver of AI growth worldwide. AVGO’s third-quarter fiscal 2025 earnings report showed ...

This article explains how to programmatically identify and deal with outlier data (it's a follow-up to "Data Prep for Machine Learning: Missing Data"). Suppose you have a data file of loan ...

An outlier is an observation that lies an abnormal distance from other values in a random sample from a population,” advises the Engineering Statistics Handbook. One of the standard approaches is to ...

Timothy E. Smetek, Kenneth W. Bauer Jr. Hyperspectral anomaly detection is a useful means for using hyperspectral imagery to locate unusual objects. Current anomaly detection methods commonly use ...

From 1992 to 2016, Ethiopia cut its stunting rate from 67 to 38 percent. The Bill & Melinda Gates Foundation has launched an Exemplars in Global Health program to learn from positive outliers like ...

After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft Research now uses a full code sample and step-by-step directions ...

Broadcom, Inc. (AVGO) up 15,109% since first Big Money outlier signal in 2011. AVGO designs, develops, and supplies semiconductors and infrastructure software solutions, proving to be a key driver of ...