Topic: easy-ensemble-classifier Goto Github
Some thing interesting about easy-ensemble-classifier
Some thing interesting about easy-ensemble-classifier
easy-ensemble-classifier,Supervised Machine Learning and Credit Risk
User: akotovets1
easy-ensemble-classifier,Perform a Credit Risk Supervised Machin Learning Analysis using scikit-learn and imbalanced-learn libraries.
User: angienoelhaverly
easy-ensemble-classifier,Supervised Machine Learning Project
User: annette-blackburn
easy-ensemble-classifier,Data preparation, statistical reasoning and machine learning are used to solve an unbalanced classification problem. Different techniques are employed to train and evaluate models with unbalanced classes.
User: ashley-green1
easy-ensemble-classifier,using machine learning to assess credit risk
User: baileerice
easy-ensemble-classifier,Supervised Machine Learning and Credit Risk
User: baylex
easy-ensemble-classifier,Supervised Machine Learning
User: biancataisepommerening
easy-ensemble-classifier,Supervised Machine Learning and Credit Risk
User: cbrito3
easy-ensemble-classifier,
User: cmmgw
easy-ensemble-classifier,Supervised machine learning model to analyze credit risk
User: cmwardcode
easy-ensemble-classifier,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.
User: dl777
easy-ensemble-classifier,Extract data provided by lending club, and transform it to be useable by predictive models.
User: ed12rivera
easy-ensemble-classifier,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
User: eric-blankinshp
easy-ensemble-classifier,Analysis of different machine learning models' performance on predicting credit default
User: ljd0
easy-ensemble-classifier,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.
User: mdbinger
easy-ensemble-classifier,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.
User: mishkanian
easy-ensemble-classifier,Uses several machine learning models to predict credit risk.
User: sarahm44
easy-ensemble-classifier,Using machine learning to train and evaluate models with unbalanced classes to determine the best models to predict credit risk.
User: shayanafzal
easy-ensemble-classifier,Predicts credit risk of individuals based on information within their application utilizing supervised machine learning models
User: showkatewang
easy-ensemble-classifier,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
User: shumph10
easy-ensemble-classifier,Creating various machine learning models to create the most accurate model to predict credit risk
User: tanmelissa
easy-ensemble-classifier,Credit Risk Analysis utilizing imbalanced classification machine learning models
User: tyedem
easy-ensemble-classifier,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.
User: yonathante
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