randomoversampler

There are 0 repository under randomoversampler topic.

cedoula / Credit_Risk_Analysis
Build and evaluate several machine learning algorithms to predict credit risk.
machine-learning oversampling undersampling randomoversampler smote machine-learning-algorithms cluster-centroids smoteenn balanced-random-forest ensemble-model logistic-regression
Language:Jupyter Notebook 6
anjalysam / Health-Insurance-Cross-Sell-Prediction
Predict Health Insurance Owners' who will be interested in Vehicle Insurance
logistic-regression xgbclassifier random-forest python datavisualization imbalanced-data randomoversampler
Language:Jupyter Notebook 5
abdoghareeb46 / NTI-Final-Assignment
NTI-Final-Assignment Use flask(python) and shiny dashboard (R) to build simple user interface to see how choosing classification model may affect prediction accuracy, using Customer Churn Dataset.
classification-algorithims data-analysis data-science flask-api imbalanced-data jupyter-notebook machine-learning machine-learning-algorithms oversampling prediction-algorithm python r randomoversampler shinydashboard smote
Language:Jupyter Notebook 3
Robertfnicholson / Credit_Risk_Analysis
Developed Machine Learning Models to Predict Credit Risk
balancedrandomforestclassifier clustercentroids clustering easyensembleclassifier machine-learning python pythonlibrarires random-forest randomoversampler smote smoteenn
Language:Jupyter Notebook 3
Sanushi-Salgado / Tumor-Teller-Prediction-Module
Prediction module for Tumor Teller - primary tumor prediction system
flask-server machinelearning-python multiclass-classification hierarchical-classification local-classifier-per-parent-node sklearn imbalanced-data imblearn matplotlib primary-tumor-classification randomoversampler
Language:Python 2
abhijha3011 / Techniques-To-Handle-Imbalanced-Data
Different Techniques to Handle Imbalanced Data Set
crossvalidation oversampling random-forest-classifier randomoversampler smote-sampling undersampling
Language:Jupyter Notebook 1
ChaitanyaC22 / Fraud_Analytics_Credit_Card_Fraud_Detection
The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.
logistic-regression svm-classifier kneighborsclassifier data-analysis decision-tree-classifier random-forest-classifier xgboost-classifier fraud-analytics banking power-transformers machine-learning-algorithms hyperparameter-optimization hyperparameter-tuning credit-card-fraud-detection smote adasyn pipelines randomoversampler imblearn oversampling
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
Malvi1497 / Credit_Risk_Analysis
To evaluate the performance of supervised machine learning models to make a written recommendation on whether they should be used to predict credit risk.
python clustercentroids imbalanced-learning jupyter-notebook machine-learning-algorithms random-forest-classifier randomoversampler scikit-learn smote supervised-learning
Language:Jupyter Notebook 1
rutujahingankar / Health-insurance-cross-sell-prediction
Predict Health Insurance Owners who will be interested in Vehicle Insurance
python random-forest logistic-regression data-visualization imbalanced-data randomoversampler xgbclassifier
Language:Jupyter Notebook 1
shaunwang1350 / CreditLoans_MachineLearning
Credit risk is an inherently unbalanced classification problem, as the number of good loans easily outnumber the number of risky loans. I employed Machine Learning techniques to train and evaluate models with unbalanced classes. I used imbalanced-learn and scikit-learn libraries to build and evaluate models using resampling. I also evaluated the performance of these models and made a recommendation on whether they should be used to predict credit risk.
classification-report credit-risk tp-fp balanced-accuracy-scores smote-sampling randomoversampler cluster-centroids random-forest
Language:Jupyter Notebook 1
AlexGeiger1 / Credit_Risk_Analysis
Python and sklearn are used to build and evaluate multiple machine learning models to predict credit risk.
ensemble-model logistic-regression machine-learning oversampling randomoversampler sklearn smote smoteenn
Language:Jupyter Notebook 0
ashwinihegde28 / Credit_Risk_Analysis
Credit_Risk_Analysis using Machine Learning
machine-learning python scikit-learn balancedrandomforestclassifier easyensembleclassifier imbalanced-learning randomoversampler smote-algorithms
Language:Jupyter Notebook 0
caseygomez / Credit_Risk_Analysis
Utilizing data preparation, statistical reasoning, and supervised machine learning to solve a real-world challenge: credit card risk.
python supervised-machine-learning balancedrandomforestclassifier clustercentroids easyensembleclassifier imbalanced-learning randomoversampler scikit-learn smote smoteenn
Language:Jupyter Notebook 0
DangCoop / Credit_Risk_Analysis
machine-learning random-forest-classifier randomoversampler smote smoteenn vscode
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
echoqshen / Credit_Risk_Analysis
Use different techniques to train and evaluate different machine learning models to predict credit risk with unbalanced classes
balancedrandomforestclassifier credit-risk machine-learning randomoversampler smote-sampling
Language:Jupyter Notebook 0
Gsilvera24 / Credit-Risk-Analysis
Credit Worthyness Analysis using Linear Regression
machine-learning randomoversampler sklearn linear-regression
Language:Jupyter Notebook 0
helenaschatz / credit-risk-classification
Using various techniques to train and evaluate a model based on loan risk. Also, using a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.
jupyter-notebook loan logistic-regression machine-learning numpy pandas python sklearn-library randomoversampler
Language:Jupyter Notebook 0
JennyJohnson78 / Credit_Risk_Analysis
Analysis using RandomOverSampler, SMOTE algorithm, ClusterCentroids algorithm, SMOTEENN algorithm, and machine learning models BalancedRandomForestClassifier and EasyEnsembleClassifier.
machine-learning randomoversampler smote clustercentroids smoteenn balancedrandomforestclassifier easyensembleclassifier
Language:Jupyter Notebook 0
lingumd / Credit_Risk_Analysis
Machine learning models for predicting credit risk in LendingClub dataset.
balancedrandomforestclassifier cluster-centroids-undersampling easyensembleclassifier imbalanced-learn machine-learning randomoversampler smote smoteenn confusion-matrix classification-report matplotlib-pyplot numpy pandas pathlib scikit-learn google-colab get-dummies
Language:Jupyter Notebook 0
minut9 / Credit_Risk_Analysis
Supervised Learning..Build/Evaluate Machine algorithms to predict credit risk
machine-learning-algorithms machine-learning logistic-regression smote oversampling undersampling clustering cluster-centroids randomoversampler smoteenn jupyter-notebook python
Language:Jupyter Notebook 0
MiracleOny / Credit-Risk-Analysis
Over- and under-sampled data using four algorithms and compared two machine learning models that reduce bias to identify the most reliable credit risk prediction model.
clustercentroids clustering-algorithm credit-risk logisticregression machine-learning matplotlib numpy oversampling-algorithms pandas randomoversampler scikit-learn seaborn smote smoteenn undersampling-algorithms
Language:Jupyter Notebook 0
NeonOstrich / Autism-Diagnosis-with-Linear-Regression-and-Neural-Networks-using-Random-Oversampling
We used a dataset that included birth and personal data as well as Autism Spectrum Quotient test scores to train machine learning algorithms to predict autism. We used Logistic Regression, Neural Network Models and Keras Tuner with Random Oversampling to train one with 90% accuracy.
keras-tuner linear-regression neural-network randomoversampler
Language:Jupyter Notebook 0
nhafer88 / Credit_Risk_Analysis
Built and evaluated variety of supervised machine learning algorithms to predict credit risk.
balanced-random-forest cluster-centroids ensemble-model logistic-regression oversampling randomoversampler smote-sampling smoteenn supervised-machine-learning undersampling
Language:Jupyter Notebook 0
Nusratnimme / Credit_Risk_Analysis
Build and evaluate several machine learning algorithms by resampling models to predict credit risk.
balanced-random-forest easyensembleclassifier machine-learning randomoversampler smote smoteenn undersampling
Language:Jupyter Notebook 0
Priya2216 / DataScience-MachineLearning-Project
Data Science Major Project Completed in IT Vedant Institute using Machine learning algorithms
python machine-learning scikit-learn naive-bayes-classifier knn-classification decsion-tree random-forest logistic-regression randomoversampler xgboost-algorithm gridsearchcv gradient-boosting eda
Language:Jupyter Notebook 0
Priya2216 / Insurance_Claim_Prediction-Neural-Network
tensorflow2 numpy pandas matplotlib seaborn sklearn dropout-keras early-stopping optimizer callback epoch dense sequential-models randomoversampler
Language:Jupyter Notebook 0
PriyankaSett / Identifying_gamma_hadron_magic_dataset
Identifying rare event.
adaboostclassifier auc curve gradient-boosting gridsearchcv matplotlib pandas pr random-forest-classifier randomoversampler roc seaborn smotetomek xgboost-classifier gmeans youden-jstatistic prcurve threshold-tuning
Language:Jupyter Notebook 0
SohrabRezaei / Credit-Risk-Analysis
I am asked to resample the credit card data since it is not balanced. First, I start to split the data and perform oversampling with RandomOverSampler and SMOTE method, and I undersample with ClusterCentroids algorithm. Then, I utilize the SMOTEENN method to oversample and undersample the data. Finally, I used ensemble models.
clustercentroids logistic-regression machine-learning smote smoteenn balancedrandomforestclassifier easyensembleclassifier randomoversampler
Language:Jupyter Notebook 0
Tobi1018 / Credit_Risk_Analysis
Analyze several machine learning algorithms to predict credit risk.
smote randomoversampler machine-learning machine-learning-algorithms logistic-regression ensemble-learning smoteenn
Language:Jupyter Notebook 0
twigikit / regression-modelling
Logistic regression model with train_test_split data
classification-report confusion-matrix logistic-regression randomoversampler supervised-machine-learning train-test-split
Language:Jupyter Notebook 0
harmanveer-2546 / Rainfall-Prediction-using-Machine-Learning
Today there are no certain methods by using which we can predict whether there will be rainfall today or not. Even the meteorological department’s prediction fails sometimes. In this project, I learn how to build a machine learning model which can predict whether there will be rainfall today or not based on some atmospheric factors.
logistic-regression machine-learning-algorithms matplotlib metrics numpy pandas python random-forest randomoversampler seaborn sklearn svm-classifier xgboost-classifier
Language:Jupyter Notebook
Harmanveer2546 / Rainfall-Prediction-using-Machine-Learning-
Today there are no certain methods by using which we can predict whether there will be rainfall today or not. Even the meteorological department’s prediction fails sometimes. In this project, I learn how to build a machine learning model which can predict whether there will be rainfall today or not based on some atmospheric factors.
logistic-regression machiine-learning-algorithms matplotlib metrics numpy pandas python random-forest randomoversampler seaborn sklearn-model svc xgboost-classifier
Language:Jupyter Notebook
kaylah176 / Credit-Risk-Classification
Objective: Address the classification problem behind predicting credit risk
classification-report confusion-matrix logistic-regression randomoversampler train-test-using-sklearn
Language:Jupyter Notebook
saraparveen26 / SupervisedLearning---Credit-Risk-Classification
This project trains and avaluates machine learning model to identify creditworthiness of borrowers and classify credit risk predictions for a peer-to-peer lending services company.
logistic-regression machine machine-learning supervised-learning supervised-machine-learning randomoversampler
Language:Jupyter Notebook

randomoversampler

cedoula / Credit_Risk_Analysis

anjalysam / Health-Insurance-Cross-Sell-Prediction

abdoghareeb46 / NTI-Final-Assignment

Robertfnicholson / Credit_Risk_Analysis

Sanushi-Salgado / Tumor-Teller-Prediction-Module

abhijha3011 / Techniques-To-Handle-Imbalanced-Data

ChaitanyaC22 / Fraud_Analytics_Credit_Card_Fraud_Detection

DougUOT / Credit_Risk_Analysis

Malvi1497 / Credit_Risk_Analysis

rutujahingankar / Health-insurance-cross-sell-prediction

shaunwang1350 / CreditLoans_MachineLearning

AlexGeiger1 / Credit_Risk_Analysis

ashwinihegde28 / Credit_Risk_Analysis

caseygomez / Credit_Risk_Analysis

DangCoop / Credit_Risk_Analysis

diercz / Credit_Risk_Analysis

echoqshen / Credit_Risk_Analysis

Gsilvera24 / Credit-Risk-Analysis

helenaschatz / credit-risk-classification

JennyJohnson78 / Credit_Risk_Analysis

lingumd / Credit_Risk_Analysis

minut9 / Credit_Risk_Analysis

MiracleOny / Credit-Risk-Analysis

NeonOstrich / Autism-Diagnosis-with-Linear-Regression-and-Neural-Networks-using-Random-Oversampling

nhafer88 / Credit_Risk_Analysis

Nusratnimme / Credit_Risk_Analysis

Priya2216 / DataScience-MachineLearning-Project

Priya2216 / Insurance_Claim_Prediction-Neural-Network

PriyankaSett / Identifying_gamma_hadron_magic_dataset

SohrabRezaei / Credit-Risk-Analysis

Tobi1018 / Credit_Risk_Analysis

twigikit / regression-modelling

harmanveer-2546 / Rainfall-Prediction-using-Machine-Learning

Harmanveer2546 / Rainfall-Prediction-using-Machine-Learning-

kaylah176 / Credit-Risk-Classification

saraparveen26 / SupervisedLearning---Credit-Risk-Classification