local-outlier-factor
There are 42 repositories under local-outlier-factor topic.
dachosen1/Feature-Engineering-for-Fraud-Detection
Implementation of feature engineering from Feature engineering strategies for credit card fraud
bharathsudharsan/COVID-away
Code for paper 'Avoid touching your face: A hand-to-face 3d motion dataset (covid-away) and trained models for smartwatches'
hibayesian/spark-lof
A parallel implementation of local outlier factor based on Spark
zhongyuchen/outlier-detection
Detect outliers with 3 methods: LOF, DBSCAN and one-class SVM
chen0040/java-local-outlier-factor
Package implements a number local outlier factor algorithms for outlier detection and finding anomalous data
Niloth-p/Density-Based-Outlier-Detection
An implementation of a density based outlier detection method - the Local Outlier Factor Technique, to find frauds in credit card transactions. For detecting both local and global outliers.
Heewon-Hailey/cyberattack-analysis
implement of ML-based anomaly detection models to identify cyberattacks from NetFlow data
mmaghajani/outlier-detection
The project is about outlier detection with different methods same as FastVOA, Kmeans, DBScan or LOF, conducted on KDD dataset.
aanchal1308/Fraud-detection
Machine learning algorithm to detect fraudulent credit card transactions
deepmancer/timeseries-anomaly-detection
Analysis of Classical Machine Learning Algorithms for Anomaly Detection in Time Series Data
nafiul-araf/Anomaly-Detection
Anomaly detection (also known as outlier analysis) is a data mining step that detects data points, events, and/or observations that differ from the expected behavior of a dataset. A typical data might reveal significant situations, such as a technical fault, or prospective possibilities, such as a shift in consumer behavior.
sheikhomar/fifi
Detecting Fake User Profiles using k-Means and Local Outlier Factor
emirka/insight
Insight Data Science DS.2019C.TO project
AjNavneet/Transaction-Fraud-Detection-Isolation-Forest-LOF
Fraud transactional detection using Isolation Forest and Local Outlier Factor (LOF) models.
Michael-Gkotsis/Local_Outlier_Factor
An implemantion of LOF Algorithm to C-lang.
natvalenz/Kronos-Geospatial
Geospatial-temporal analysis using Holoviews, along with Pandas to combine various types of data in sensible ways to describe common daily routines for GASTech employees and identify up to twelve unusual events or patterns in the data.
Pradnya1208/Credit-card-fraud-detection-using-Isolation-Forest-and-LOF
This project aims to detect credit card fraud using Anamoly detection techniques such as Isolation Forest and Local Outlier Factor algorithms.
PriyabrataThatoi/Anomaly-Detection---IF-LOF
Anomaly detection using unsupervised method is a challenging one. Isolated Random Forest and Local Outlier Factor are the most promising one. They detect outlier with highest recall possible.
Xenia101/Local-Outlier-Factor
Deriving the Local Outlier Factor Score
YoNG-Zaii/Casting-Products-Defects-Detection
Anomaly detection using IF, LOF, OC-SVM, Autoencoder.
c-gauffre/PyGoodVibes
détection non supervisée de sons anormaux
EricSchoebel/LpzHackathon2023
KI-Analysetool für die Stadtentwicklung in Leipzig, Gewinner des Leipzig Open Data Hackathons 2023 / AI analysis tool for urban development in Leipzig, winner of the Leipzig Open Data Hackathon 2023 (for English, see README-en.md)
haldersourav/anomaly-detection
Comparison of various anomaly detection algorithms using scikit-learn and visualization through Plotly Dash
imtej/CC_Fraud-Detection-Project-for-AFAME-TECHNOLOGIES
Credit Card Fraud Detection: An ML project on credit card fraud detection using various ML techniques to classify transactions as fraudulent or legitimate. This project involves data analysis, preparation, and use of models like Logistic regression, KNN, Decision Trees, Random Forest, XGBoost, and SVM, along with various oversampling technique.
kkrusere/Credit-Card-Fraud-Anomaly-Outlier-Detection
The project explores a range of methods, including both statistical analysis, traditional machine learning and deep learning approaches to anomaly detection a critical aspect of data science and machine learning, with a specific application to the detection of credit card fraud detection and prevention.
LeilaMoussa/_lof
My undergrad research programming sandbox + Capstone project
Mittalkabir/-Credit-Card-Fraud-Detection
Fraud Detection model based on anonymized credit card transactions based on Isolation Forest Algorithm and Local Outlier Factor
nurhabibrs/local-outlier-factor-java
Tugas Besar Mata Kuliah Data Miining
rajeevvhanhuve/Credit-Card-Anomaly-Detection
Anomaly Detection
hoomanbing/Outlier-Detection-and-Removal-from-Multimedia
Detection and removal of specific types of outliers present in different data formats which includes detection and removal of contextual outliers from textual data using LOF, outliers from tabular numeric data using LOF, gaussian noise from image data using NLM.
PARAVPREET17/Credit-Card-Fraud-Detection
Fraud Detection model based on anonymized credit card transactions based on Isolation Forest Algorithm and Local Outlier Factor