falaybeg/SparkStreaming-Network-Anomaly-Detection

This repository includes supervised and unsupervised machine learning methods which are used to detect anomalies on network datasets. Decision Tree, Random Forest, Gradient Boost Tree, Naive Bayes, and Logistic Regression were used for supervised learning. K-Means was used for unsupervised learning.

语言：Jupyter Notebook · GitHub 星标：18 · Fork：5

话题：anomaly-detection · classification · clustering · decision-tree · intrusion-detection · machine-learning · pyspark · spark-streaming

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