Skip to content

guptashivam27/Anomaly-Detection

Repository files navigation

AnomalyDetection

Identification of anomalies in various dataset involves analysis of various datasets and finding patterns that do not conform to a model of "normal" behaviour. This has been performed using K-means clustering algorithm. Further the accuracy of the results produced by K-means is improved by using Random Forest Classifier.

About

It involves analysis of various datasets in order to find patterns that do not conform to a model of “normal” behavior. The main moto of this project is to combine the strengths of two different algorithms in order to produce an algorithm with better accuracy rate. This has been performed using scikit learn implementation of K-means clustering a…

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors