Ecosyste.ms: Repos
An open API service providing repository metadata for many open source software ecosystems.
GitHub topics: easy-ensemble-classifier
Akotovets1/Credit_Risk_Analysis
Supervised Machine Learning and Credit Risk
Language: Jupyter Notebook - Size: 216 KB - Last synced: 4 months ago - Pushed: about 2 years ago - Stars: 0 - Forks: 0
Angienoelhaverly/Credit_Risk_Analysis
Perform a Credit Risk Supervised Machin Learning Analysis using scikit-learn and imbalanced-learn libraries.
Language: Jupyter Notebook - Size: 18.4 MB - Last synced: 8 months ago - Pushed: about 3 years ago - Stars: 1 - Forks: 1
LJD0/Credit_Risk_Analysis
Analysis of different machine learning models' performance on predicting credit default
Language: Jupyter Notebook - Size: 18.4 MB - Last synced: about 1 year ago - Pushed: about 1 year ago - Stars: 0 - Forks: 0
cbrito3/Credit_Risk_Analysis
Supervised Machine Learning and Credit Risk
Language: Jupyter Notebook - Size: 986 KB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
sarahm44/credit-risk-predictor
Uses several machine learning models to predict credit risk.
Language: Jupyter Notebook - Size: 9.54 MB - Last synced: over 1 year ago - Pushed: almost 2 years ago - Stars: 1 - Forks: 0
showkatewang/Credit_Risk_Analysis
Predicts credit risk of individuals based on information within their application utilizing supervised machine learning models
Language: Jupyter Notebook - Size: 646 KB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
BaileeRice/Credit_Risk_Analysis
using machine learning to assess credit risk
Language: Jupyter Notebook - Size: 18.4 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
eric-blankinshp/Credit_Risk_Analysis_Supervised_ML
About Six different techniques are employed to train and evaluate models with unbalanced classes. Algorithms are used to predict credit risk. Performance of these different models is compared and recommendations are suggested based on results. Topics
Language: Jupyter Notebook - Size: 18.5 MB - Last synced: about 1 year ago - Pushed: over 1 year ago - Stars: 0 - Forks: 0
tanmelissa/Credit_Risk_Analysis
Creating various machine learning models to create the most accurate model to predict credit risk
Language: Jupyter Notebook - Size: 16.6 KB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 0 - Forks: 0
shumph10/Credit_Risk_Analysis
Established a supervised machine learning model trained and tested on credit risk data through a variety of methods to establish credit risk based on a number of factor
Language: Jupyter Notebook - Size: 39.6 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago - Stars: 0 - Forks: 0
mdbinger/Credit_Risk_Analysis
Built, trained and evaluated multiple supervised machine learning algorithms to predict credit risk for loan applicants. Algorithms ran include Random Oversampler, SMOTE, Cluster Centroids, SMOTEENN, Balanced Random Forest Classifier, and Easy Ensemble Classifier.
Language: Jupyter Notebook - Size: 18.5 MB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 0 - Forks: 0
tyedem/Risky_Business
Credit Risk Analysis utilizing imbalanced classification machine learning models
Language: Jupyter Notebook - Size: 16.8 MB - Last synced: 4 months ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0
YonathanTE/Machine-Learning
Compared the effectiveness of the EasyEnsembleClassifier and LogisticRegression libraries. This was to assess the model with the best scores for balanced accuracy, recall, and geometric mean.
Language: Jupyter Notebook - Size: 17 MB - Last synced: about 1 year ago - Pushed: about 2 years ago - Stars: 0 - Forks: 0
Baylex/Credit_Risk_Analysis
Supervised Machine Learning and Credit Risk
Language: Jupyter Notebook - Size: 20.8 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 11
jharvey09/solana_sentinment_analysis Fork of MetaDJ/solana_sentinment_analysis
For this analysis, we used computational linguistics and biometrics to systematically identify the trend using various news articles and closing prices using the "CoinGecko CSV & Crypto News API"!
Size: 73.2 KB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0
DL777/Risky_Business
Using machine learning (ML) models to predict credit risk using data typically analysed by peer-to-peer lending services. Resampling data with SMOTE, Cluster Centroids, SMOTEENN and applying ensemble learning classifiers: Balanced Random Forest Classifier and Easy Ensemble Classifier.
Language: Jupyter Notebook - Size: 626 KB - Last synced: 19 days ago - Pushed: over 3 years ago - Stars: 0 - Forks: 0