smote-oversampler

There are 0 repository under smote-oversampler topic.

nive927 / Flight_Delay_Prediction
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 two-stage flight-delay-prediction pre-processing data-cleaning data-visualization airports forecasts flights feature-selection feature-extraction correlation-coefficient feature-ranking auc-roc-curve performance-metrics pipelining smote smote-oversampler random-under-sampling imbalanced-classes
Language:Jupyter Notebook 14
MsTao-68 / Debt-Churn-Data-Analysis
使用比赛方提供的脱敏数据，进行客户信贷流失预测。
machine-learning xgboost-model ann autogluon eda tabnet lightgbm smote-oversampler smote-sampling stacking-classifier stacking-ensemble stratified-cross-validation stratified-sampling
Language:Jupyter Notebook 6
edaaydinea / OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data
This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.
anova-analysis catboost-classifier chi-square-test data-science deep-learning keras-neural-networks lightgbm-classifier logistic-regression machine-learning multi-layer-perceptron-classifier neural-networks random-forest-classifier smote-oversampler tensorflow xgboost-classifier
Language:Jupyter Notebook 5
Kaushikjas10 / Liquefaction-XGBoost-SHAP-Jas-Dodagoudar
This repository is associated with interpretable/explainable ML model for liquefaction potential assessment of soils. This model is developed using XGBoost and SHAP.
artificial-intelligence boosting extreme-gradient-boosting geotechnical-engineering liquefaction machine-learning matlab python shapley-additive-explanations explainable-machine-learning kmeans-smote smote smote-oversampler synthetic-dataset-generation
Language:Jupyter Notebook 3
MoinDalvs / Assignment_Decision_Tree_2
adasyn-sampling data-science decision-trees imbalanced-data smote-oversampler smoteenn smotetomek
Language:Jupyter Notebook 2
ChriStingo / HeartDisease-Analysis-and-Prediction
Data analysis, visualization and prediction for the prevention of heart disease using ML models
data-science data-analysis machine-learning random-forest knn smote-oversampler roc-auc machine-learning-algorithms data-visualization heart-disease-prediction
Language:Jupyter Notebook 1
DougUOT / Credit_Risk_Analysis
We'll use Python to build and evaluate several machine learning models to predict credit risk. Being able to predict credit risk with machine learning algorithms can help banks and financial institutions predict anomalies, reduce risk cases, monitor portfolios, and provide recommendations on what to do in cases of fraud.
machine-learning python pandas numpy scikit-learn jupyter-notebook randomoversampler logistic-regression confusion-matrix classification-report smote-oversampler balancedrandomforestclassifier easyensembleclassifier centroids smoteenn
Language:Jupyter Notebook 1
Hands-On-Fraud-Analytics / Chapter-12-Data-Preparation-for-Fraud-Analytics
Chapter 12: Data Preparation for Fraud Analytics
algorithms classification classificationreport creditcard feature-scaling fraud heatmap imbalanced-data logistic-regression-classifier machine-learning matplotlib modelling onehot-encoding optimization-algorithms pandas performance-metrics random-forest-classifier seaborn smote-oversampler
Language:Jupyter Notebook 1
Kenner82 / Credit_Risk_Analysis
Testing 6 different machine learning models to determine which is best at predicting credit risk.
ada-boost-classifier balanced-random-forest cluster-centroid-undersampling ensemble-learning naive-random-oversampler oversampling-algorithms smote-oversampler smoteenn-combination combination-sampling-algorithms undersampling-algorithms pandas python supervised-machine-learning
Language:Jupyter Notebook 1
mmsaki / credit-risks-ml
Using the imbalanced-learn and Scikit-learn libraries to build and evaluate machine learning models.
balanced-accuracy-scores classification-models credit-risk imbalanced-classification imbalanced-learning loan-prediction-analysis logistic-regression machine-learning oversampling predictive-modeling resampling sklearn smote-oversampler smoteenn-combination undersampling-technique
Language:Jupyter Notebook 1
Sar-Go / Adult-Income-Prediction-AzureMLStudio
Future Ready Talent Project Submission.Using Azure ML Studio to predict the income of individuals, based on their age, race, education, residence city, etc. Used the adult census dataset
azure-machine-learning-studio boosted-decision-trees adult-census-income smote-oversampler split-datasets
1
Sidessh / Multi-Class-Classification---License-Status-Prediction
Multi-class Classification - License Status Prediction
decision-trees imbalanced-data knn-classification logistic-regression multiclass-classification naive-bayes-classifier smote-oversampler xgboost-classifier
Language:Jupyter Notebook 1
TrungLuong1194 / breast-cancer-classification
deep-learning convolutional-neural-networks cancer-detection machine-learning pytorch pca-analysis image-classification google-collab smote-oversampler augmentation
Language:Jupyter Notebook 1
utsavchaudharygithub / Credit_Risk_Analysis
Credit risk is an inherently unbalanced classification problem, as good loans easily outnumber risky loans. Therefore, we needed to employ different techniques to train and evaluate models with unbalanced classes. Jill asks us to use imbalanced-learn and scikit-learn libraries to build and evaluate models using resampling
ensemble-machine-learning machine-learning-algorithms random-forest resampling-methods smote-oversampler smote-sampling
Language:Jupyter Notebook 1
No_Show_Appointment_ML-Logistic-Regression-
Zarich12 / No_Show_Appointment_ML-Logistic-Regression-
Predicts if a patient will show up at a scheduled appointment based on certain features.
data-science imbalanced-learning logistic-regression machine-learning smote-oversampler
Language:Jupyter Notebook 1
AjayKrishna76 / CreditCard_Fraud_Detection_UsingML
Detect Fraudulent Credit Card transactions using different Machine Learning models
cnn-keras decision-tree-classifier fraud-detection gradient-boosting-classifier keras-wrapper mlp-classifier random-forest-classifier smote-oversampler tensorflow
Language:Jupyter Notebook 0
Anil-account / Heart-Disease-Prediction
heartdisease-prediction jupyter-notebook machine-learning randomforest accuracy confusion-matrix knn naive-bayes roc smote-oversampler
Language:Jupyter Notebook 0
AyushTyagi1610 / Credit-Risk-Modelling
Built a model to determine the risk associated with extending credit to a borrower. Performed Univariate and Bivariate exploration using various methods such as pair-plot and heatmap to detect outliers and to monitor the behaviour and correlation of the features. Imputed the missing values using KNN Imputer and implemented SMOTE to address the imbalanced data. Trained the model using KNN, Decision Trees, Logistic Regression and Random Forest to achieve the best accuracy of 93%.
datacleaning knn-imputer pandas python random-forest smote-oversampler visualisation
Language:Jupyter Notebook 0
BaileeRice / Credit_Risk_Analysis
using machine learning to assess credit risk
machine-learning balanced-random-forest easy-ensemble-classifier naive-random-oversampler smote-oversampler undersampling
Language:Jupyter Notebook 0
cbrito3 / Credit_Risk_Analysis
Supervised Machine Learning and Credit Risk
ada-boost-classifier balanced-random-forest cluster-centroids-undersampling easy-ensemble-classifier imbalance-learning machine-learning machine-learning-algorithms naive-random-oversampler over-sampling precision-recall scikit-learn scikitlearn-machine-learning smote-oversampler under-sampling
Language:Jupyter Notebook 0
DavidNart90 / KNUST-BreastCancer-Prediction
This repository contains the resources and codebase for a research project aimed at predicting breast cancer cases using data from the KNUST hospital.
breast-cancer-prediction classification decision-trees neural-network random-forest smote-oversampler tradeoff-analysis xgboost-classifier
Language:Jupyter Notebook 0
diercz / Credit_Risk_Analysis
Utilized several machine learning models to predict credit risk using Python's imbalanced-learn and scikit-learn libraries
clustercentroids creditrisk-analysis easyensembleclassifier machine-learning random-forest-classifier randomoversampler smote-oversampler smoteenn
Language:Jupyter Notebook 0
FarhanaTeli / Kyphosis_Disease_Prediction_with_FCNN_XGBoost
Kyphosis disease prediction using Fully Connected Neural Networks (FCNNs) model and XGBoost model with GridSearchCV
adam-optimizer binaryclassification binarycrossentropy disease-prediction gridsearchcv hyperparameter-tuning imbalanced-data labelencoding neural-network numpy pandas python pytorch sklearn smote-oversampler standardization xgboost-classifier
Language:Jupyter Notebook 0
Leohrithik / Titanic-Survival-Prediction
Survival prediction using Four Different kind of algorithms and optimizing the dataset using PCA and SMOTE
decision-tree-classifier knearest-neighbor-classifier pca prediction-model random-forest-classifier smote-oversampler svc
Language:Jupyter Notebook 0
LJD0 / Neural_Network_Charity_Analysis
A Deep Learning analysis to predict success of charity campaigns
cluster-centroids-undersampling deep-learning machine-learning neural-network pandas python smote-oversampler
Language:Jupyter Notebook 0
maengjulie / Battery-Degradation-Analysis-Project-code
Battery analysis project
lowess smote-oversampler statistical-testing
Language:Python 0
Olatohun / loan-default
classification-algorithm ensemble f1-score smote-oversampler
Language:Jupyter Notebook 0
rud-ninja / Imbalanced_binary_classification
improving correct classification of class with less representation
confusion-matrix hyperparameter-tuning random-forest-classifier smote-oversampler
Language:Jupyter Notebook 0
Rutgers-Data-Science-Bootcamp / Credit_Risk_Analysis
Data preparation, Statistical reasoning, Machine Learning
ensemble-machine-learning oversampling-algorithms scikitlearn-machine-learning smote-oversampler smoteenn-combination undersampling
Language:Jupyter Notebook 0
credit-risk-predictor
sarahm44 / credit-risk-predictor
Uses several machine learning models to predict credit risk.
balanced-random-forest cluster-centroids cluster-centroids-undersampling credit-risk easy-ensemble-classifier ensemble-learning fintech logistic-regression machine-learning naive-random-oversampler random-forest resampling smote smote-oversampler smoteenn-combination
Language:Jupyter Notebook 0
annette-blackburn / Credit_Risk_Analysis
Supervised Machine Learning Project
balanced-random-forest easy-ensemble-classifier imbalanced-learning machine-learning naive-random-oversampler scikit-learn smote-oversampler undersampling combination-under-over-sampling
Language:Jupyter Notebook
Bahey1200022 / Credit-Card-Fraud-Detection
solution https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud. Xgboost is an efficient method of gradient boosting that makes a random initial prediction then calculates similarity scores and gain to build the trees and decrease the gap between the actual value and the predicted value.Gridsearch was used to get the best parameters tuning.
gridsearchcv smote-oversampler xgboost-algorithm
Language:Jupyter Notebook
DivyaSudagoni / Predicting-hotel-booking-cancellation
This project predicts hotel booking cancellations using Machine Learning techniques, benefiting both travelers and hotels.
decision-tree-classifier knn-classification python smote-oversampler extratreesclassifier
Language:Jupyter Notebook
Hands-On-Fraud-Analytics / Chapter-11-Handling-Imbalanced-Data-Sets
Handling Imbalanced Data Sets
best-practices colab fraud imbalanced-data machine-learning python smote-oversampler
Language:Jupyter Notebook
MinaShirinchi / AI-class-1402
Here is the repository for sharing jupyter notebooks discussed in 'AI-1402' class.
smote-oversampler classification-evaluation
Language:Jupyter Notebook
tanmelissa / Credit_Risk_Analysis
Creating various machine learning models to create the most accurate model to predict credit risk
cluster-analysis easy-ensemble-classifier machine-learning random-forest smote-oversampler smoteenn
Language:Jupyter Notebook

smote-oversampler

nive927 / Flight_Delay_Prediction

MsTao-68 / Debt-Churn-Data-Analysis

edaaydinea / OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data

Kaushikjas10 / Liquefaction-XGBoost-SHAP-Jas-Dodagoudar

MoinDalvs / Assignment_Decision_Tree_2

ChriStingo / HeartDisease-Analysis-and-Prediction

DougUOT / Credit_Risk_Analysis

Hands-On-Fraud-Analytics / Chapter-12-Data-Preparation-for-Fraud-Analytics

Kenner82 / Credit_Risk_Analysis

mmsaki / credit-risks-ml

Sar-Go / Adult-Income-Prediction-AzureMLStudio

Sidessh / Multi-Class-Classification---License-Status-Prediction

TrungLuong1194 / breast-cancer-classification

utsavchaudharygithub / Credit_Risk_Analysis

Zarich12 / No_Show_Appointment_ML-Logistic-Regression-

AjayKrishna76 / CreditCard_Fraud_Detection_UsingML

Anil-account / Heart-Disease-Prediction

AyushTyagi1610 / Credit-Risk-Modelling

BaileeRice / Credit_Risk_Analysis

cbrito3 / Credit_Risk_Analysis

DavidNart90 / KNUST-BreastCancer-Prediction

diercz / Credit_Risk_Analysis

FarhanaTeli / Kyphosis_Disease_Prediction_with_FCNN_XGBoost

Leohrithik / Titanic-Survival-Prediction

LJD0 / Neural_Network_Charity_Analysis

maengjulie / Battery-Degradation-Analysis-Project-code

Olatohun / loan-default

rud-ninja / Imbalanced_binary_classification

Rutgers-Data-Science-Bootcamp / Credit_Risk_Analysis

sarahm44 / credit-risk-predictor

annette-blackburn / Credit_Risk_Analysis

Bahey1200022 / Credit-Card-Fraud-Detection

DivyaSudagoni / Predicting-hotel-booking-cancellation

Hands-On-Fraud-Analytics / Chapter-11-Handling-Imbalanced-Data-Sets

MinaShirinchi / AI-class-1402

tanmelissa / Credit_Risk_Analysis