Data Science Dojo

JULY 15, 2024

K-Nearest Neighbors (KNN): This method classifies a data point based on the majority class of its K nearest neighbors in the training data. These anomalies can signal potential errors, fraud, or critical events that require attention. Points far away from others are considered anomalies.

Machine Learning 308

Machine Learning Machine Learning Algorithm Clustering 308

PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Spectral clustering, a technique rooted in graph theory, offers a unique way to detect anomalies by transforming data into a graph and analyzing its spectral properties.

Clustering 56

Clustering Algorithm Machine Learning Machine Learning 56

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

IBM Journey to AI blog

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements. But what is an anomaly and why is detecting it important?

Machine Learning 91

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 91

Pickl AI

SEPTEMBER 3, 2023

Observations that deviate from the majority of the data are known as anomalies and might take the shape of occurrences, trends, or events that differ from customary or expected behaviour. Finding anomalous occurrences that might point to intriguing or potentially significant events is the aim of anomaly detection.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52