GitHub topics: imbalanced-learn
Hemanth-072/Stroke-Risk-Prediction-Using-Machine-Learning
Machine-learning pipeline for predicting stroke risk from patient health and lifestyle data.
Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0
IFTE-13/Early-Stage-Brain-Stroke-Detection
Predictive Analysis & Early Detection of Brain stroke using Machine Learning Algorithm
Language: Jupyter Notebook - Size: 2.36 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0
ZhiningLiu1998/self-paced-ensemble
[ICDE'20] ⚖️ A general, efficient ensemble framework for imbalanced classification. | 泛用，高效，鲁棒的类别不平衡学习框架
Language: Python - Size: 1.44 MB - Last synced at: 6 days ago - Pushed at: over 1 year ago - Stars: 258 - Forks: 50
kochlisGit/ProphitBet-Soccer-Bets-Predictor
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.
Language: Python - Size: 3.47 MB - Last synced at: 29 days ago - Pushed at: 3 months ago - Stars: 389 - Forks: 132
IFTE-13/Loan-Approval-System
Loan Approval System
Language: Jupyter Notebook - Size: 837 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
ZhiningLiu1998/mesa
[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
Language: Jupyter Notebook - Size: 1.62 MB - Last synced at: 29 days ago - Pushed at: 11 months ago - Stars: 106 - Forks: 26
Danish-Jamil-01/kidney-tumor-detection
Demonstrating how changes in input image resolution affect the algorithm's output
Size: 1.78 GB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 1
MatthieuLeNozach/insurance_classification_imalanced
Binary classification from a dataset with imbalanced target feature classes
Language: Python - Size: 48.5 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
ttsudipto/recurrence-pred-genomics
ML-based prediction of NSCLC recurrence with gene expression data
Language: Python - Size: 11.1 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0
zoj613/pyloras
Experimental implementations of several (over/under)-sampling techniques not yet available in the imbalanced-learn library.
Language: Python - Size: 4.99 MB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 12 - Forks: 3
alexandrazhuu/Shopping-Intentions
What causes a shopper to hit "purchase"?
Language: Jupyter Notebook - Size: 1.27 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
daze0/data-intensive-final-project
Final project for the end of the course in collaboration with Alessandro Zanzi.
Language: Jupyter Notebook - Size: 2.13 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
TaylortheGenie/insurance_claims
A full stack classification machine learning project.
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zunicd/Bank-Churn-Prediction
Bank customers churn dashboard with predictions from several machine learning models.
Language: Jupyter Notebook - Size: 9.37 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 18 - Forks: 28
00ber/review-score-prediction-amazon-fine-food
Review score prediction using text on the Amazon Fine Food dataset
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
ArtTucker/Credit_Risk_Analysis
Credit risk analysis using scikit-learn and imbalanced-learn.
Language: Jupyter Notebook - Size: 19.2 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 1
Dimara-Delmar/Credit_Risk_Analysis
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.
Language: Jupyter Notebook - Size: 18.6 MB - Last synced at: 3 months ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
kheller18/credit_risk_resampling
Machine learning app to identify credit risk
Language: Jupyter Notebook - Size: 574 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
mrcreasey/oc-ds-p7-scoring-dashboard
Conception and deployment of a credit-scoring model, API and interactive dashboard
Language: Jupyter Notebook - Size: 58.3 MB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
maronem/Credit_Risk_Analysis
Testing different supervised machine learning algorithms to predict credit risk
Language: Jupyter Notebook - Size: 18.4 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0
rivas-j/Credit_Risk_Analysis-Machine-Learning
Utilizing Machine Learning to Analyze and Assess Credit Risk
Language: Jupyter Notebook - Size: 38 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
SohaT7/NYC_Restaurant_Analysis Fork of Veronicaywl/Final_Project
Data visualization of the NYC restaurant data, and data analysis to gauge if a restaurant located in a high-income area receives a higher health inspection grade. Uses Python (Pandas, Scikit-learn, Imbalanced-learn), PostgreSQL, SQLAlchemy, Tableau, JavaScript (Plotly.js library), HTML, CSS, and Bootstrap.
Language: JavaScript - Size: 58.2 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
lingumd/Credit_Risk_Analysis
Machine learning models for predicting credit risk in LendingClub dataset.
Language: Jupyter Notebook - Size: 26.6 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
ksommerdorf/SupervisedML
A case study utilizing supervised machine learning. (In order for the code to work, unzip the csv file in the Resources folder)
Language: Jupyter Notebook - Size: 18.4 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0
sainigagandeep/Credit_Risk_Analysis
Identify credit card risk using Machine Learning algorithms
Language: Jupyter Notebook - Size: 580 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
SohaT7/Credit_Risk_Analysis
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.
Language: Jupyter Notebook - Size: 19.4 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
zobairhas/Credit_Risk_Analysis
Predict credit risk using a variety of Resampling Models and algorithms.
Language: Jupyter Notebook - Size: 37.9 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
tyedem/Risky_Business
Credit Risk Analysis utilizing imbalanced classification machine learning models
Language: Jupyter Notebook - Size: 16.8 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0
