Topic: imbalanced-learn Goto Github
Some thing interesting about imbalanced-learn
Some thing interesting about imbalanced-learn
imbalanced-learn,Review score prediction using text on the Amazon Fine Food dataset
User: 00ber
imbalanced-learn,Data analysts were asked to examine credit card data from peer-to-peer lending services company LendingClub in order to determine credit risk. Supervised machine learning was employed to find out which model would perform the best against an unbalanced dataset. Data analysts trained and evaluated several models to predict credit risk.
User: acfthomson
imbalanced-learn,What causes a shopper to hit "purchase"?
User: alexandrazhuu
imbalanced-learn,Credit risk analysis using scikit-learn and imbalanced-learn.
User: arttucker
imbalanced-learn,
User: cmmgw
imbalanced-learn,Demonstrating how changes in input image resolution affect the algorithm's output
User: danish-jamil-01
imbalanced-learn,Final project for the end of the course in collaboration with Alessandro Zanzi.
User: daze0
imbalanced-learn,Using six different machine learning algorithms to evaluate credit data and compare each model’s accuracy, precision, and recall scores in relation to the data’s credit risk.
User: dimara-delmar
imbalanced-learn,Predict credit risk with machine learning techniques.
User: dldmarnell
imbalanced-learn,Предсказание оттока клиентов из банка
User: egorumaev
imbalanced-learn,Built and evaluated several machine-learning models to predict credit risk using free data from LendingClub.
User: herose07
imbalanced-learn,Credit risk is an unbalanced classification problem, as the number of good loans easily outnumber the number of risky loans. Use imbalanced-learn and scikit-learn libraries to build and evaluate machine learning models using resampling.
User: hhnguyenn
imbalanced-learn,Machine learning app to identify credit risk
User: kheller18
imbalanced-learn,Use Python and Scikit-learn and Imbalanced-learn to predict credit risk. Compare the strengths and weaknesses of machine learning models. Assess how well a model works.
User: kobertlam
imbalanced-learn,ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.
User: kochlisgit
imbalanced-learn,A case study utilizing supervised machine learning. (In order for the code to work, unzip the csv file in the Resources folder)
User: ksommerdorf
imbalanced-learn,Machine learning models for predicting credit risk in LendingClub dataset.
User: lingumd
imbalanced-learn,Testing different supervised machine learning algorithms to predict credit risk
User: maronem
imbalanced-learn,Binary classification from a dataset with imbalanced target feature classes
User: matthieulenozach
imbalanced-learn,
User: mazinonsa
imbalanced-learn,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
imbalanced-learn,Conception and deployment of a credit-scoring model, API and interactive dashboard
User: mrcreasey
imbalanced-learn,Utilizing Machine Learning to Analyze and Assess Credit Risk
User: rivas-j
imbalanced-learn,Identify credit card risk using Machine Learning algorithms
User: sainigagandeep
imbalanced-learn,Supervised machine learning models built and evaluated to predict credit loan risk. Resampling and ensemble techniques applied to the logistic regression classifier models using Scikit-learn, Imbalanced-learn, Pandas, and NumPy libraries in Python.
User: sohat7
imbalanced-learn,Predict credit risk with machine learning models by using different techniques to train and evaluate models with unbalanced classes.
User: sydscorner
imbalanced-learn,A full stack classification machine learning project.
User: taylorthegenie
imbalanced-learn,Credit Risk Analysis utilizing imbalanced classification machine learning models
User: tyedem
imbalanced-learn,NeurIPS’20 | Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题
User: zhiningliu1998
Home Page: https://arxiv.org/abs/2010.08830
imbalanced-learn,ICDE'20 | A general & effective ensemble framework for imbalanced classification. | 泛用,高效,鲁棒的类别不平衡学习框架
User: zhiningliu1998
Home Page: https://arxiv.org/abs/1909.03500v3
imbalanced-learn,Predict credit risk using a variety of Resampling Models and algorithms.
User: zobairhas
imbalanced-learn,Bank customers churn dashboard with predictions from several machine learning models.
User: zunicd
Home Page: https://bank-churn-predictions.onrender.com
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