Topic: easyensembleclassifier Goto Github
Some thing interesting about easyensembleclassifier
Some thing interesting about easyensembleclassifier
easyensembleclassifier,Built several supervised machine learning models to predict the credit risk of candidates seeking loans.
User: abdullahbera
easyensembleclassifier,Analyze of several Machine Learning techniques in order to help Jill decide on a most effective Machine Learning Model to analyze Credit Card Risk applications.
User: abidor13
easyensembleclassifier,An analysis on credit risk
User: ajmnd
easyensembleclassifier,Credit_Risk_Analysis using Machine Learning
User: ashwinihegde28
easyensembleclassifier,Utilizing data preparation, statistical reasoning, and supervised machine learning to solve a real-world challenge: credit card risk.
User: caseygomez
easyensembleclassifier,Banking-Dataset-Marketing-Targets
User: daiphuongngo
easyensembleclassifier,Utilized several machine learning models to predict credit risk using Python's imbalanced-learn and scikit-learn libraries
User: diercz
easyensembleclassifier,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.
User: douguot
easyensembleclassifier,Train and evaluate models to determine credit card risk using a credit card dataset
User: dylansteinhauer
easyensembleclassifier,Analyzing credit card risk with machine learning models!
User: ekanpat
easyensembleclassifier,Testing various supervised machine learning models to predict a loan applicant's credit risk.
User: jbalooshie
easyensembleclassifier,Analysis using RandomOverSampler, SMOTE algorithm, ClusterCentroids algorithm, SMOTEENN algorithm, and machine learning models BalancedRandomForestClassifier and EasyEnsembleClassifier.
User: jennyjohnson78
easyensembleclassifier,Machine learning models for predicting credit risk in LendingClub dataset.
User: lingumd
easyensembleclassifier,Utilized several machine learning models to predict credit risk using Python's imbalanced-learn and scikit-learn libraries
User: nicoserrano
easyensembleclassifier,Build and evaluate several machine learning algorithms by resampling models to predict credit risk.
User: nusratnimme
easyensembleclassifier,Determine supervised machine learning model that can accurately predict credit risk using python's sklearn library. Python, Pandas, imbalanced-learn, skikit-learn
User: ramya-ramamur
easyensembleclassifier,Credit risk is an inherently unbalanced classification problem, as good loans easily outnumber risky loans. Therefore, you’ll need to employ different techniques to train and evaluate models with unbalanced classes. Using the credit card credit dataset from LendingClub, a peer-to-peer lending services company,
User: rl16193
easyensembleclassifier,Developed Machine Learning Models to Predict Credit Risk
User: robertfnicholson
easyensembleclassifier,Apply machine learning to solve the challenge of credit risk
User: sjwedlund
easyensembleclassifier,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.
User: sohrabrezaei
easyensembleclassifier,Using machine learning to determine which model is best at predicting credit risk amongst random oversampling, SMOTE, ClusterCentroids, SMOTEENN, Balanced Random Forest, or Easy Ensemble Classifier (AdaBoost).
User: stephperillo
easyensembleclassifier,Supervised Machine Learning Project: imbalanced-learn; scikit-learn; RandomOverSampler; SMOTE; ClusterCentroids; SMOTEENN; BalancedRandomForestClassifier; EasyEnsembleClassifier.
User: weihaolun
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