creditrisk-analysis

There are 1 repository under creditrisk-analysis topic.

• cdfq384903 / MonotonicOptimalBinning

  This project mainly implements the Monotonic Optimal Binning(MOB) algorithm in SAS 9.4. We extend the application of this algorithm which can be applied to numerical and categorical data. In order to avoid the problem of creating too many bins, we optimize the p-value iteratively and provide bins size first binning, monotonicity first binning, and chi merge binning methods for users to discretize data more conveniently.

  mobsasrisk-managementmonotonic-optimal-binningdata-discretizationcreditcreditriskcreditrisk-analysismonotone
  Language:SAS 9

• barkamoljon / PortfolioProjects

  Projects

  absenteeismamazonwebscrapecovid-19creditrisk-analysiscustomeranalysislinear-regressionlogistic-regressionsqltableaupowerbideep-learningmachine-learningpython
  Language:Jupyter Notebook 3

• sahidul-shaikh / credit-analytics-student-loan

  Analysis of the student loans data to determine, if there are any loan characteristics that are predictive of the Early Risk Score.

  creditrisk-analysisedapythonexploratory-data-analysisstudent-loans
  Language:Jupyter Notebook 2

• a-memme / Credit_Risk_Analysis

  Comparing sampling techniques and classification algorithms to predict credit risk

  machine-learningpython3numpypandassci-kit-learnsampling-methodsundersamplingoversamplingcreditrisk-analysisrandom-forest-classifiertree-modelslogistic-regression
  Language:Jupyter Notebook 1

• CAPS-project / CreditRisk-Analysis

  take csv file loan_data_2007_2014,loan_data_2015,loan_data_2007_2014_preprocessed,loan_data_inputs_2015,loan_data_inputs_test,loan_data_inputs_train.csv from banklife line

  creditrisk-analysis
  Language:Jupyter Notebook 1

• TrilaksonoBS / Credit-Risk-Management-by-Using-Machine-Learning

  In this project, we wanna create Credit Risk Management by using Machine Learning, so we dig into the data. what we do for the next steps are Data Preparation, EDA(Exploratory Data Analysis), Data Visualization, Data Preprocessing (Handling Outliers, Missing Value, Feature Encoding, Standardization, and Normalization), Creating Machine Learning Model with few algorithms, Evaluation Model, looking for Feature Importance, gain insight, and create a recommendation for Credit Risk Management

  creditcreditriskcreditrisk-analysisdecision-treedecission-tree-classifierlogistic-regressionmachine-learningmachine-learning-algorithmsregressionregression-modelsrisk-analysisrisk-management
  Language:Jupyter Notebook 1

• YourOriginal / AI-Credit-Risk

  Applying various sampling methods and ML to analyze credit risk

  creditcreditrisk-analysismachine-learning
  Language:Jupyter Notebook 1

• AnvithaChaluvadi / Credit-Risk_Module12Challenge

  I will use various techniques to train and evaluate models with imbalanced classes.

  creditcreditrisk-analysismodule-12-supervised-learninganalysislogistic-regressionrandom-over-samplingvalue-count
  Language:Jupyter Notebook 0

• diercz / Credit_Risk_Analysis

  Utilized several machine learning models to predict credit risk using Python's imbalanced-learn and scikit-learn libraries

  clustercentroidscreditrisk-analysiseasyensembleclassifiermachine-learningrandom-forest-classifierrandomoversamplersmote-oversamplersmoteenn
  Language:Jupyter Notebook 0

• nicoserrano / Credit_Risk_Analysis

  Utilized several machine learning models to predict credit risk using Python's imbalanced-learn and scikit-learn libraries

  machine-learningsmote-oversamplerrandomoversamplerclustercentroidssmoteennrandom-forest-classifiereasyensembleclassifiercreditrisk-analysis
  Language:Jupyter Notebook 0