All Projects → Feature-Engineering-for-Fraud-Detection → Similar Projects or Alternatives

342 Open source projects that are alternatives of or similar to Feature-Engineering-for-Fraud-Detection

gouda
Golang Utilities for Data Analysis
Stars: ✭ 18 (-41.94%)
Mutual labels:  kmeans, dbscan
MemStream
MemStream: Memory-Based Streaming Anomaly Detection
Stars: ✭ 58 (+87.1%)
text clustering
文本聚类(Kmeans、DBSCAN、LDA、Single-pass)
Stars: ✭ 230 (+641.94%)
Mutual labels:  kmeans, dbscan
deepAD
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on J…
Stars: ✭ 65 (+109.68%)
DGFraud-TF2
A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X
Stars: ✭ 84 (+170.97%)
Pyod
A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Stars: ✭ 5,083 (+16296.77%)
benfordslaw
benfordslaw is about the frequency distribution of leading digits.
Stars: ✭ 29 (-6.45%)
Remixautoml
R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.
Stars: ✭ 159 (+412.9%)
msda
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
Stars: ✭ 80 (+158.06%)
A-Detector
⭐ An anomaly-based intrusion detection system.
Stars: ✭ 69 (+122.58%)
Machine Learning Workflow With Python
This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation
Stars: ✭ 157 (+406.45%)
Mutual labels:  kmeans, feature-engineering
kmeans-dbscan-tutorial
A clustering tutorial with scikit-learn for beginners.
Stars: ✭ 20 (-35.48%)
Mutual labels:  kmeans, dbscan
AnomalyDetection
基于智能计算框架nupic的异常检测restful Api.
Stars: ✭ 31 (+0%)
Mutual labels:  anomaly-detection
KMeans elbow
Code for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'
Stars: ✭ 35 (+12.9%)
Mutual labels:  kmeans
exemplary-ml-pipeline
Exemplary, annotated machine learning pipeline for any tabular data problem.
Stars: ✭ 23 (-25.81%)
Mutual labels:  feature-engineering
sherlock
Sherlock is an anomaly detection service built on top of Druid
Stars: ✭ 137 (+341.94%)
Mutual labels:  anomaly-detection
sioyek
Sioyek is a PDF viewer designed for reading research papers and technical books.
Stars: ✭ 3,890 (+12448.39%)
Mutual labels:  research-paper
NVTabular
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
Stars: ✭ 797 (+2470.97%)
Mutual labels:  feature-engineering
CCD
Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]
Stars: ✭ 30 (-3.23%)
Mutual labels:  anomaly-detection
ml-simulations
Animated Visualizations of Popular Machine Learning Algorithms
Stars: ✭ 33 (+6.45%)
Mutual labels:  kmeans
XGBOD
Supplementary material for IJCNN paper "XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning"
Stars: ✭ 59 (+90.32%)
Mutual labels:  anomaly-detection
EvolutionaryForest
An open source python library for automated feature engineering based on Genetic Programming
Stars: ✭ 56 (+80.65%)
Mutual labels:  feature-engineering
TabFormer
Code & Data for "Tabular Transformers for Modeling Multivariate Time Series" (ICASSP, 2021)
Stars: ✭ 209 (+574.19%)
Mutual labels:  fraud-detection
CARE-GNN
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
Stars: ✭ 121 (+290.32%)
Mutual labels:  fraud-detection
anomalib
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.
Stars: ✭ 1,210 (+3803.23%)
Mutual labels:  anomaly-detection
zca
ZCA whitening in python
Stars: ✭ 29 (-6.45%)
Mutual labels:  feature-engineering
fuzzymax
Code for the paper: Don't Settle for Average, Go for the Max: Fuzzy Sets and Max-Pooled Word Vectors, ICLR 2019.
Stars: ✭ 43 (+38.71%)
Mutual labels:  research-paper
PubMed-Best-Match
Machine-learning based pipeline relying on LambdaMART currently used in PubMed for relevance (Best Match) searches
Stars: ✭ 36 (+16.13%)
Mutual labels:  feature-engineering
Rough-Sketch-Simplification-Using-FCNN
This is a PyTorch implementation of the the Paper by Simo-Sera et.al. on Cleaning Rough Sketches using Fully Convolutional Neural Networks.
Stars: ✭ 31 (+0%)
Mutual labels:  research-paper
ReinforcementLearning Sutton-Barto Solutions
Solutions and figures for problems from Reinforcement Learning: An Introduction Sutton&Barto
Stars: ✭ 20 (-35.48%)
Mutual labels:  feature-engineering
Quora-Paraphrase-Question-Identification
Paraphrase question identification using Feature Fusion Network (FFN).
Stars: ✭ 19 (-38.71%)
Mutual labels:  feature-engineering
data-science-popular-algorithms
Data Science algorithms and topics that you must know. (Newly Designed) Recommender Systems, Decision Trees, K-Means, LDA, RFM-Segmentation, XGBoost in Python, R, and Scala.
Stars: ✭ 65 (+109.68%)
Mutual labels:  kmeans
xgboost-smote-detect-fraud
Can we predict accurately on the skewed data? What are the sampling techniques that can be used. Which models/techniques can be used in this scenario? Find the answers in this code pattern!
Stars: ✭ 59 (+90.32%)
Mutual labels:  fraud-detection
favorite-research-papers
Listing my favorite research papers 📝 from different fields as I read them.
Stars: ✭ 12 (-61.29%)
Mutual labels:  research-paper
skrobot
skrobot is a Python module for designing, running and tracking Machine Learning experiments / tasks. It is built on top of scikit-learn framework.
Stars: ✭ 22 (-29.03%)
Mutual labels:  feature-engineering
A-Hierarchical-Transformation-Discriminating-Generative-Model-for-Few-Shot-Anomaly-Detection
Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"
Stars: ✭ 42 (+35.48%)
Mutual labels:  anomaly-detection
featuretoolsOnSpark
A simplified version of featuretools for Spark
Stars: ✭ 24 (-22.58%)
Mutual labels:  feature-engineering
dominance-analysis
This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.
Stars: ✭ 111 (+258.06%)
Mutual labels:  feature-engineering
anomagram
Interactive Visualization to Build, Train and Test an Autoencoder with Tensorflow.js
Stars: ✭ 152 (+390.32%)
Mutual labels:  anomaly-detection
AutoTabular
Automatic machine learning for tabular data. ⚡🔥⚡
Stars: ✭ 51 (+64.52%)
Mutual labels:  feature-engineering
Bagel
IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder
Stars: ✭ 45 (+45.16%)
Mutual labels:  anomaly-detection
CGvsPhoto
Computer Graphics vs Real Photographic Images : A Deep-learning approach
Stars: ✭ 24 (-22.58%)
Mutual labels:  research-paper
ocsvm-anomaly-detection
anomaly detection by one-class SVM
Stars: ✭ 66 (+112.9%)
Mutual labels:  anomaly-detection
SIFT-BoF
Feature extraction by using SITF+BoF.
Stars: ✭ 22 (-29.03%)
Mutual labels:  kmeans
ClusterR
Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering
Stars: ✭ 69 (+122.58%)
Mutual labels:  kmeans
topic modelling financial news
Topic modelling on financial news with Natural Language Processing
Stars: ✭ 51 (+64.52%)
Mutual labels:  dbscan
skmeans
Super fast simple k-means implementation for unidimiensional and multidimensional data.
Stars: ✭ 59 (+90.32%)
Mutual labels:  kmeans
ind knn ad
Industrial knn-based anomaly detection for images. Visit streamlit link to check out the demo.
Stars: ✭ 102 (+229.03%)
Mutual labels:  anomaly-detection
coursera-ml-py-sj
No description or website provided.
Stars: ✭ 41 (+32.26%)
Mutual labels:  anomaly-detection
CVAE-AnomalyDetection-PyTorch
Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)
Stars: ✭ 23 (-25.81%)
Mutual labels:  anomaly-detection
COVID-away
Repo of paper title 'Avoid touching your face: A hand-to-face 3d motion dataset (covid-away) and trained models for smartwatches'
Stars: ✭ 18 (-41.94%)
Mutual labels:  local-outlier-factor
MachineLearning
Implementations of machine learning algorithm by Python 3
Stars: ✭ 16 (-48.39%)
Mutual labels:  kmeans
minionn
Privacy -preserving Neural Networks
Stars: ✭ 58 (+87.1%)
Mutual labels:  research-paper
traffic
A quick and dirty vehicle speed detector using video + anomaly detection
Stars: ✭ 21 (-32.26%)
Mutual labels:  anomaly-detection
AutoTS
Automated Time Series Forecasting
Stars: ✭ 665 (+2045.16%)
Mutual labels:  feature-engineering
ailia-models
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Stars: ✭ 1,102 (+3454.84%)
Mutual labels:  anomaly-detection
kaggle-berlin
Material of the Kaggle Berlin meetup group!
Stars: ✭ 36 (+16.13%)
Mutual labels:  feature-engineering
clustering-python
Different clustering approaches applied on different problemsets
Stars: ✭ 36 (+16.13%)
Mutual labels:  kmeans
PANDA
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation (CVPR 2021)
Stars: ✭ 64 (+106.45%)
Mutual labels:  anomaly-detection
deviation-network-image
Official PyTorch implementation of the paper “Explainable Deep Few-shot Anomaly Detection with Deviation Networks”, weakly/partially supervised anomaly detection, few-shot anomaly detection, image defect detection.
Stars: ✭ 47 (+51.61%)
Mutual labels:  anomaly-detection
1-60 of 342 similar projects