random-under-sampling

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Tek-nr /AI-Based-Fraud-Detection

Star38

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

UpdatedFeb 25, 2024
Jupyter Notebook

nive927 /Flight_Delay_Prediction

Star24

A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.

machine-learning data-visualization feature-selection performance-metrics feature-extraction forecasts pipelining flights airports data-cleaning smote correlation-coefficient pre-processing auc-roc-curve imbalanced-classes two-stage feature-ranking flight-delay-prediction smote-oversampler random-under-sampling

UpdatedJan 10, 2024
Jupyter Notebook

rochitasundar /Predictive-maintenance-cost-minimization-using-ML-ReneWind

Star22

The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.

pipeline cross-validation classification-algorithims sklearn-metrics randomizedsearchcv train-validation-test smote-sampling random-under-sampling

UpdatedJan 20, 2022
Jupyter Notebook

shalakasaraogi /credit-card-fraud-detection

Star3

Credit card fraud detection using machine learning techniques

credit-card ros smote fraud-detection random-over-sampling random-under-sampling synthetic-minority-over-sampling

UpdatedOct 21, 2020
R

santiagoahl /breast-cancer-prediction

Star3

Machine Learning model API deployed with GCP & DVC. Predicts a breast-cancer diagnostic.

css html docker gcp angular-cli logistic-regression kaggle-dataset breast-cancer fastapi random-under-sampling

UpdatedJun 9, 2023
Jupyter Notebook

AvinandanBose /Credit-Card-Fraud-Detection-Machine-Learning-

Star1

Credit Card Fraud Detection using Python and Machine Learning.

python machine-learning machine-learning-algorithms credit-card seaborn artificial-intelligence pca logistic-regression matplotlib decision-trees support-vector-machines creditcard oversampling matplotlib-pyplot stratified-cross-validation quantile-transformer smote-sampling random-over-sampling random-under-sampling tomek-link-elimination

UpdatedJan 2, 2022
Jupyter Notebook

sharmasapna /credit-card-fraud-detection

Star1

Code to detect credit card fraud detecton

random-forest dnn xgboost accuracy logistic-regression outlier-detection decision-trees autoencoders credit-cards k-means-clustering isolation-forest tsne-plot fraudulent-transactions recall-precision tsne-visualization smote-sampling random-over-sampling random-under-sampling fraud-transactions transaction-numbers

UpdatedJul 19, 2021
Jupyter Notebook

manjugovindarajan /RENEWIND-predictive-maintenance-cost-maintenance-usingML

Star0

The aim is to decrease maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionizing model using pipelines

pipeline cross-validation classification-algorithims sklearn-metrics randomizedsearchcv train-validation-test smote-sampling random-under-sampling

UpdatedOct 10, 2023
Jupyter Notebook

TienNguyen93 /diabetes-prediction

Star0

Implement a suite of ML algorithms to improve diabetes prediction

machine-learning random-forest xgboost pca logistic-regression multilayer-perceptron gridsearchcv stratified-sampling linear-svc smote-sampling random-under-sampling

UpdatedJan 3, 2025
Jupyter Notebook

bushra-ansari /Predicting-Term-Deposit-Subscription-by-a-Client-by-SVM-Classifier

Star0

Support Vector Machine Classification model is applied on bank dataset containing 41188 rows and 21 columns. The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (b…

correlation exploratory-data-analysis support-vector-machine dummies hyperparameter-tuning boxplot svm-classifier imbalanced-data feature-scaling bivariate-analysis univariate-analysis categorical-predictors random-under-sampling model-evaluation-metrics