Robust Cardinality Estimator by Non-autoregressive Model
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Updated
Apr 25, 2022 - Python
Robust Cardinality Estimator by Non-autoregressive Model
Exploratory data analysis of 2 datasets
This project is part of my studies @ Otto-von-Guericke University, Magdeburg
Some Algoithms to Count Unique Elements
Cardinality estimation with local models
Self-Tuning GPU-Accelerated Kernel Density Estimators
A Rust implementation of the CVM algorithm for counting distinct elements in a stream
Cardinality Estimation Benchmark
go-cardinality is a Go library that calculates the cardinality and distinct count of values in a dataset, providing efficient and accurate estimations.
This repository provides streaming algorithms that can be used for monitoring large-scale data streams.
Estimating cardinality for a data stream using Go and Apache Kafka
Updated code for different query featurizations for MSCN
Distributed Cardinality Tracking
UltraLogLog: A Practical and More Space-Efficient Alternative to HyperLogLog for Approximate Distinct Counting
HyperLogLog en C++ y OpenMP para cálculo de similitud de genomas mediante índice de Jaccard
Reference implementation of the Affirmative Sampling algorithm by Jérémie Lumbroso and Conrado Martínez (2022). 🍀
python implementations of the Flajolet-Martin, LogLog, SuperLogLog, and HyperLogLog cardinality estimation algorithms, specifically used to estimate the cardinality of unique traffic violations in NYC in the 2019 fiscal year
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