huyunsheng121

huyunsheng121's Stars

• noise-lab/netml

  Feature Extraction and Machine Learning from Network Traffic Traces

  Language:Python5416

• vnetman/pcap2csv

  Use PyShark and scapy to read fields from a pcap file and populate a CSV

  Language:Python5323

• daud99/FlowGenerator

  This is the python implementation of CICFlowMeter which aims to produce CSV based flow provided the network interface and PCAPs.

  Language:Python21

• thilak-kanala/DDoS-Detect

  Detect DDoS attack network traffic from PCAP file using machine learning.

  Language:Python137

• neyney10/PCAPFeatureExtractor

  Feature extraction from PCAP files.

  Language:Python53

• Bingmang/pcap2kdd

  A kddcup99 features extractor.

  Language:Bro85

• AI-IDS/kdd99_feature_extractor

  Utility for extraction of subset of KDD '99 features from realtime network traffic or .pcap file

  Language:C++11949

• kaushalshetty/SMOTE

  Synthetic Minority Over-sampling Technique

  Language:Python3621

• Yasir-ali-farrukh/Payload-Byte

  Payload-Byte is a tool for extracting and labeling packet capture (Pcap) files of modern network intrusion detection datasets.

  Language:Jupyter Notebook212

• liyang328/H-SMOTE

  Language:Jupyter Notebook2

• Jung-Alen/IW-SMOTE

  Instance Weighted SMOTE by Indirectly Exploring the Data Distribution

  Language:Python61

• AnonAuthorAI/duplebalance

  DuBE: Duple-balanced Ensemble Learning from Skewed Data

  Language:Python85

• qm19/A-Weakly-Supervised-Learning-based-Oversampling-Framework-for-Imbalanced-Classification

  This is a program of a new weakly supervised learning based oversampling framework to solve the imbalanced classification proposed by Min Qian and Yanfu Li.

  Language:Python73

• gkapatai/MaatPy

  Language:Jupyter Notebook1410

• canoalberto/ROSE

  ROSE: Robust Online Self-Adjusting Ensemble for Continual Learning from Imbalanced Drifting Data Streams

  Language:Java82

• analyticalmindsltd/smote_variants

  A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features

  Language:Jupyter Notebook615138

• prgc/ps-des

  Source code used in the research paper "A Post-Selection Algorithm for Improving Dynamic Ensemble Selection Methods"

  Language:Python1

• KaiHuangMO/RCSMOTE

  Code for RCSMTE(https://www.sciencedirect.com/science/article/abs/pii/S0020025520306794)

  2

• PiotrKowalski/msi-projekt

  University project for "Artificial intelligence methods". The comparison of DES-kNN, KNORA-U, KNORA-E and ADABoost

  Language:Python1

• KhalifaSeck/IMPLEMENTATION-FROM-SCRATCH-DES-KNN-VOISINS

  Language:Jupyter Notebook2

• ciszko/DES_KNN

  Language:Python1

• marianaasouza/lords

  Code used in the experiments of the paper entitled Local overlap reduction procedure for dynamic ensemble selection, to be presented at the IJCNN 2022

  Language:Python2

• domingos108/solar_forecasting

  the source code of the paper named as: Solar Irradiance forecasting using dynamic ensemble selection

  Language:Python121

• w4k2/ECML19-IoT-DES-preproc

  Language:Python11

• MLDMXM2017/ECOC_DES

  Language:Python1

• Jesen-BT/DES-ICD

  The source code of paper "Dynamic Ensemble Selection for Imbalanced Data Streams with Concept Drift"

  Language:Python11

• samplesvdd/sample_svdd

  A sampling SVDD algorithm for large datasets.

  Language:Python1711

• jeroenvansaane/Deep-Learning-Based-Intrusion-Detection-NSL-KDD

  Deep Learning based Intrusion Detection on NSL-KDD Dataset

  Language:Jupyter Notebook111

• omar-rh/NIDS-based-on-DL-with-imbalanced-NSL-KDD

  the DL methods used are : DNN, CNN, LSTM, GRU, CNN-LSTM, CNN-GRU, CNN-BiLSTM, CNN-BiGRU, the dataset used is : imbalanced NSL-KDD (KDDTrain+, KDDTest20+)

  Language:Jupyter Notebook323

• pgl19thu/ACACM-Autoencoder-and-Confidence-Assisted-Classificaiton-Model

  network anomaly detection

  Language:Python3