Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook
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Dec 7, 2022 - Jupyter Notebook
#
adasyn
Here are 43 public repositories matching this topic...
A fraud detection project that processes user or credit card data using machine learning and deep learning algorithms.
machine-learning deep-learning smote fraud-detection adasyn random-over-sampling random-under-sampling
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Feb 25, 2024 - Jupyter Notebook
Credit Card Fraud Detection Project
random-forest svm xgboost logistic-regression decision-trees knn smote adasyn kfold-cross-validation credit-risk
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Jul 19, 2020 - Jupyter Notebook
This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.
machine-learning artificial-intelligence classification evaluation-metrics augmentation imbalanced-data smote evaluation-framework synthetic-data adasyn synthetic-dataset-generation copulas ctgan
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Aug 8, 2022 - Python
MATLAB code for augmenting small datasets using EigenSample
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Feb 23, 2020 - MATLAB
The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.
machine-learning-algorithms pipelines banking hyperparameter-optimization data-analysis logistic-regression hyperparameter-tuning decision-tree-classifier svm-classifier smote oversampling kneighborsclassifier random-forest-classifier power-transformers adasyn imblearn credit-card-fraud-detection randomoversampler xgboost-classifier fraud-analytics
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Jan 24, 2023 - Jupyter Notebook
Location information about commuter activities is vital for planning for travel disruptions and infrastructural development. The Mobility Sensing Project aims to find innovative and novel ways to identify travel patterns from GPS data and other multi-sensory data collected in smartphones. This will be transformative to provide personalised trave…
aws sklearn s3-bucket python3 naive-bayes-classifier classification hyperopt boto3 smote adasyn datascience-machinelearning lightgbm-models randomforest-classification
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Dec 17, 2022 - Jupyter Notebook
Data Science Case Study
python machine-learning random-forest flask-application smote gradient-boosting adasyn adaboost-learning
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Jul 29, 2018 - Python
python jupyter-notebook data-transformation feature-selection scratch feature-scaling information-gain adasyn imbalance-dataset min-max-normalization
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Aug 21, 2020 - Jupyter Notebook
Using Random undersampling, Tomeklinks, Random oversampling, SMOTE, SMOTE+Tomeklinks and ADASYN from inbuilt imbalanced learn library and found how many records added or discarded.
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Oct 21, 2024 - Jupyter Notebook
This repository contains the code for baseline model replication along with all experiments and used datasets as part of the master's thesis on the topic "Detecting Dyslexia Using Deep Learning".
machine-learning deep-learning random-forest neural-networks phonology support-vector-machines k-nearest-neighbours dyslexia smote adasyn online-gamified-test
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Sep 4, 2023 - Jupyter Notebook
The computing scripts associated with our paper entitled "Oversampling Highly Imbalanced Indoor Positioning Data using Deep Generative Models".
bluetooth-low-energy fingerprinting smote oversampling recurrence-plot variational-autoencoder conditional-vae adasyn
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Aug 30, 2021 - Python
This repository contains the code, documentation, and datasets for a comprehensive exploration of machine learning techniques to address class imbalance. The project investigates the impact of various methods, like ADASYN, KMeansSMOTE, and Deep Learning Generator, on classification performance while effectively demonstrating benefits of pipelining.
deep-learning pipeline cross-validation eda feature-selection classification data-preprocessing class-imbalance data-cleaning hyperparameter-tuning data-pipeline oversampling synthetic-data adasyn kmeanssmote
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Jul 15, 2024 - Jupyter Notebook
The case study is a traditional supervised binary classification problem based on the UCI Machine Learning Repository "adult" dataset.
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Jun 6, 2022 - Jupyter Notebook
Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.
machine-learning counter pipeline random-forest feature-selection classification imbalanced-data smote adasyn imblearn sklearn-metrics smotetomek grid-search-cv standard-scaler assignment-15
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Feb 5, 2023 - Jupyter Notebook
Detecting Abnormal Markets - Early Warning Systems
python machine-learning statistics timeseries time-series matlab knn smote anomaly-detection adasyn early-warning-system borderline-smote early-warning-s
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Jul 11, 2022 - HTML
To predict whether the customers will subscribe to the system after 1-month free trial or not.
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Feb 22, 2019 - Jupyter Notebook
Classification of Obesity Status in Indonesia Using XGBoost & ADASYN-N Method
machine-learning rstudio feature-selection xgboost decision-tree boosting obesity adasyn ensemble-machine-learning
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Apr 17, 2022 - R
Implementation of augmentation, SMOTE, ADASYN, AE, DGAN for oversampling image data used in detection (YOLO and others one stage detectors). Maritime flags/code scenario.
machine-learning deep-learning pytorch autoencoder research-paper augmentation imbalanced-data smote ssd300 adasyn ssd512 maritime-data-science imbalanced-classification dgans yolov7 yolov8
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Dec 21, 2024 - Python
Classify Indonesian Obesity Status using ADASYN-N and Random Forest algorithm
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Jun 11, 2022 - Jupyter Notebook
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