find outliers in a dataset
TypeScript definitions for outliers
Fit a model to noisy data by excluding outliers. This is an implementation of the RANSAC algorithm.
Grubbs' test for outliers
Grubbs' test for outliers.
Moving Grubbs' test for outliers.
Detect outliers in callback delays.
Suggests outliers based on IQR
Hampel filter for removing outliers from time series data
Remove outliers in maps or 2D cartesian coordinate systems
Find outliers in dataset
get a array without outliers
Real-time anomalies(outliers) detection system for periodic time series
Detect outliers in callback delays.
Detect anomalies and outliers in data
MCP server for data analytics and chart insights — detect trends, outliers, correlations, generate executive summaries, and recommend optimal visualizations for datasets
Identifies patterns and outliers in large log files and structured data
Takes a FeatureCollection of points and calculates the median center.
Sample addresses to figure out if a host + port is consistent
MCP server for data preparation and transformation — parse CSV/JSON, clean datasets, compute aggregations, detect outliers, pivot tables, and prepare data for chart visualization with ChartForge
Data Visualization is the graphical representation of information and data . By doing so , it provides an accessable way to see and understand trends , outliers and patterns in the data .
Lightweight statistics package: mean, median, standard deviation, correlation, linear regression, z-table, outliers detection, and more
Basic statistics functions
The visualization provides three views with distinct processing of collected data - a subset of features that define the trainee behavior and enable us to explore outliers or trainee strategies during their gameplay.
Identify outliers in a data set.
An exploration of various sorting algorithms
BlaKE12: Blazing-fast KEccak on 12 rounds
Rust library for generating and rendering mazes
Fast `&[u8]` to integer parser
This crate provides a way to monitor the usage for a set of crates.io crates
Outlier detection for time series.
An implementation of the Isolation Forest anomoly detection algorithm.
Outlier detection pattern for Tower services - fleet-aware instance ejection
A bit vector with the Rust standard library's portable SIMD API
A simple outlier detection in 2D paths taken
A high-performance Rust-based disk cleanup tool that finds duplicates and storage outliers
Configuraiton verification framework.
Read more documentation at repository homepage.
Explainable outlier/anomaly detection for Ruby
Detect outliers in high-dimension data sets using the FASTOUT algorithm by Foss et. al
Outlier/anomaly detection for Ruby using Isolation Forest
Outlier Detection with One-class SVM
Basic statistical functions for Ruby collections, such as mean, standard_deviation, z, and outlier detection
A Ruby gem that extends all Enumerable objects (Arrays, Ranges, Sets, etc.) with essential statistical methods. Provides mean, median, variance, and standard deviation calculations, along with robust outlier detection using the IQR method. Perfect for data analysis, performance monitoring, A/B testing, and cleaning datasets with extreme values. Zero dependencies and works seamlessly with any Ruby collection that includes Enumerable.
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