Topic: balanced-accuracy-scores Goto Github
Some thing interesting about balanced-accuracy-scores
Some thing interesting about balanced-accuracy-scores
balanced-accuracy-scores,This project aims to predict credit risk using various ensemble machine learning techniques. I have also tried to handle imbalance by using various sampling methods.
User: devinaa1604
balanced-accuracy-scores,Performed feature engineering, cross-validation (5 fold) on baseline and cost-sensitive (accounting for class imbalance) Decision trees and Logistic Regression models and compared performance. Used appropriate performance metrics i.e., AUC ROC, Average Precision and Balanced Accuracy. Outperformed baseline model.
User: karthikvadlamani
balanced-accuracy-scores,Use Python to build and evaluate several machine learning models to predict credit risk for FinTech firms.
User: klaudio07
balanced-accuracy-scores,Using the imbalanced-learn and Scikit-learn libraries to build and evaluate machine learning models.
User: mmsaki
balanced-accuracy-scores,A predictive model to anticipate customer churn in telecom. Using supervised ML techniques, it identifies at-risk customers based on usage patterns and service plans. Proactively retaining customers, reducing attrition costs.
User: parita2442
balanced-accuracy-scores,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.
User: shaunwang1350
balanced-accuracy-scores,Module 12 - Using the imblearn , I'll use a logistic regression model to compare 2 versions of a dataset. First, I’ll use the original data. Next, I’ll resample the data by using RandomOverSampler. In both cases, I’ll get the count of the target classes, train a logistic regression classifier, calculate the balanced accuracy score, generate a con
User: shayleaschreurs
balanced-accuracy-scores,Supervised machine learning on lending and credit risk.
User: tienl
balanced-accuracy-scores,Resampling exercise to predict accuracy, precision, and sensitivity in credit-loan risk
User: tracari
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