imblearn

There are 2 repositories under imblearn topic.

GenTaylor / Traffic-Accident-Analysis
Traffic Accident Analysis using python machine learning
analysis imbalanced-data imblearn lightgbm machine-learning prediction python scikit-learn tableau visualizations
Language:Jupyter Notebook 20
sharmaroshan / Fraud-Detection-in-Insurace-Claims
This is a very Important part of Data Science Case Study because Detecting Frauds and Analyzing their Behaviours and finding reasons behind them is one of the prime responsibilities of a Data Scientist. This is the Branch which comes under Anamoly Detection.
balanced-random-forest data-visualization imbalanced-data imbalanced-learning imblearn jupyter-notebook python sklearn target-encoding
Language:Jupyter Notebook 10
pratik-choudhari / Intent-classification-using-python
Imbalanced Intent classification model with deployment
intent-classification python imblearn heroku machine-learning
Language:JavaScript 4
binaryvexjuiit / Detecting-Facial-Diseases-Through-Neural-Networks
Facial skin disease detection using Neural Networks
glob imblearn keras matplotlib-pyplot numpy python3 seaborn tensorflow
Language:Python 3
hdkronke / cc-customer-attrition-project
Machine learning is used to analyze and predict attrition flags in credit card customers.
jupyter-notebook machine-learning imblearn matplotlib numpy pandas scipy seaborn sklearn sqlite
Language:Jupyter Notebook 3
kalyaniasthana / CS273A_project_diabetes
Course Project for CS273A: Machine Learning at UCI
machine-learning scikit-learn smote-sampling neural-networks diabetes uci logistic-regression random-forest feature-engineering uci-machine-learning imblearn
Language:Jupyter Notebook 3
nnilayy / Classification-Notebook
Data Science Classification General Notebook
imbalanced-data imblearn machine-learning multiclass-classification scikit-learn
Language:Jupyter Notebook 2
Sanushi-Salgado / Tumor-Teller-Prediction-Module
Prediction module for Tumor Teller - primary tumor prediction system
flask-server machinelearning-python multiclass-classification hierarchical-classification local-classifier-per-parent-node sklearn imbalanced-data imblearn matplotlib primary-tumor-classification randomoversampler
Language:Python 2
shayleaschreurs / Machine-Learning-Trading-Bot
Our goal was to create a ML bot that analyzes real time trading data to determine the most opportune times buy and sell stock
alpaca-trading-api hvplot imblearn ipython-display matplotlib pandas pathlib pydotplus python sklearn finta
Language:Jupyter Notebook 2
spapicchio / Gamma-Telescope-Analysis
Machine Learning analysis for an imbalanced dataset. Developed as final project for the course "Machine Learning and Intelligent Systems" at Eurecom, Sophia Antipolis
imbalance-classification svm-classifier random-forest ablation-study learning-curves roc-curves imblearn
Language:Jupyter Notebook 2
AJMnd / Credit_Risk_Analysis
An analysis on credit risk
balancedrandomforestclassifier clustercentroids easyensembleclassifier get-dummies imbalanced-learning imblearn logistic-regression python random-over-sampling scikit-learn smote smoteenn supervised-machine-learning
Language:Jupyter Notebook 1
alessandrosocc / Machine-Learning-Project-2022
Final project of the Machine Learning course at the University of Cagliari in 2022. Analysis of a dataset, use of Machine Learning techniques with Oversampling and Undersampling techniques. Final report with the results obtained.
imblearn machine-learning matplotlib-pyplot oversampling pandas scikit-learn spambase-dataset undersampling
Language:Python 1
ChaitanyaC22 / Fraud_Analytics_Credit_Card_Fraud_Detection
The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.
logistic-regression svm-classifier kneighborsclassifier data-analysis decision-tree-classifier random-forest-classifier xgboost-classifier fraud-analytics banking power-transformers machine-learning-algorithms hyperparameter-optimization hyperparameter-tuning credit-card-fraud-detection smote adasyn pipelines randomoversampler imblearn oversampling
Language:Jupyter Notebook 1
clairempr / spooky-classify
Text classification with scikit-learn, used to make predictions for Kaggle Spooky Author Identification competition
python scikit-learn scikitlearn-machine-learning machine-learning text-classification nlp-machine-learning nlp spacy imbalanced-learning pandas kaggle matplotlib pyplot seaborn imblearn smote
Language:Python 1
cp-PYFOREST / PYFOREST-ML
Utilizing machine learning to examine deforestation rates in the undeveloped region of Paraguay's Chaco
deforestation machine-learning random-forest land-use-plan paraguay predictive-modeling forest-prediction policy-analysis forest-management geospatial geospatial-data deforestation-risk deforestation-model python imblearn balancedrandomforestclassifier geospatial-analysis geospatial-machine-learning geospatial-predictions
Language:Jupyter Notebook 1
ImMaxRoss / predicting_churn
Building a classifier model workflow with pipeline.
data-science imblearn machine-learning machine-learning-algorithms modeling pipeline python3 scikit-learn
Language:Jupyter Notebook 1
NaveenKumarMaurya / datascience-project-portfolio
Portfolio of my data science projects which i have completed for learning, skill development .
python data-visualization nlp classification-algorithm supervised-learning unsupervised-learning sklearn nltk seaborn matplotlib statistics imblearn plotly scipy
Language:Jupyter Notebook 1
npantfoerder / credit-risk-analysis
Using Scikit-learn and Imbalanced-learn to build and evaluate ML models that predict credit risk
python jupyter-notebook scikit-learn imblearn credit-risk ml-models smote cluster-centroids-algorithm smoteenn random-forest ensemble-classifier oversampling supervised-machine-learning undersampling
Language:Jupyter Notebook 1
prohogiy90 / ds-model-of-the-behavior-of-the-SberAvtopodpiska-customers
This repository contain my final projekt on the Data science Skillbox school on the topic: "Development of a machine learning algorithm to predict the behavior of customers of the "SberAvtopodpiska"
catboost eda histgram-gradient-boosting imbalanced-data imblearn jupyter-notebook lgbmclassifier pipeline python sber skillbox stacking-classifier data-science machine-learning
Language:Jupyter Notebook 1
SayamAlt / Fraudulent-Transactions-Prediction
Successfully trained a machine learning model which can predict whether a given transaction is fraud or not.
data-visualization exploratory-data-analysis imblearn machine-learning model-based-testing model-building predictive-analytics sklearn
Language:Python 1
shanuhalli / Assignment-Random-Forest
Use Random Forest to prepare a model on fraud data. Treating those who have taxable income <= 30000 as "Risky" and others are "Good" and A cloth manufacturing company is interested to know about the segment or attributes causes high sale.
adasyn classification counter feature-selection grid-search-cv imbalanced-data imblearn machine-learning pipeline random-forest sklearn-metrics smote smotetomek standard-scaler assignment-15
Language:Jupyter Notebook 1
shinho123 / 23.11.10-1st-Korean-Society-of-Industrial-Engineers
2023년 11월 대한산업공학회(UNIST) : 다중 역할 경험을 고려한 게임 유저 이탈 예측: 롤 게임을 중심으로, 1저자
api-data churn-user-prediction data-preprocessing imblearn league-of-legends machine-learning-classification numpy pandas pickle riot-api sklearn imbalanced-data json-api
Language:Jupyter Notebook 1
SpaceFrostDev / telco_kaggle
Building a tabular binary classification neural network to predict Telco's Customer Churn from their publicly available dataset on Kaggle.
deep-learning pytorch sklearn imblearn pandas
Language:Jupyter Notebook 1
adkwn1 / predict_customer_churn
Classification task for machine laerning models to predict customer churn for a telecom company. Includes EDA, work plan, and model training/evaluation/comparison.
catboost classification-models data-visualization decision-tree exploratory-data-analysis lightgbm numpy pandas pipeline scaling sklearn smote imblearn
Language:Jupyter Notebook 0
alaa-aleryani / Credit_Risk_Classification
We used various techniques to train and evaluate a model based on loan risk. We used a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.
imblearn numpy pandas pathlib sklearn sklearn-metrics sklearn-model supervised-machine-learning imblearn-metrics
Language:Jupyter Notebook 0
egorumaev / 2023-cirrhosis-outcomes
Прогнозирование исхода лечения пациентов с циррозом печени
catboost iqr lda matplotlib numpy pandas pca phik pipeline sklearn t-sne xgboost imblearn
Language:Jupyter Notebook 0
jianninapinto / Bandersnatch
This project implements a machine learning model using Random Forest, XGBoost, and Support Vector Machines algorithms with oversampling and undersampling techniques to handle imbalanced classes for classification tasks in the context of predicting the rarity of monsters.
python mongodb pymongo altair imbalanced-classification imblearn machine-learning oversampling random-forest-classifier scikit-learn smote support-vector-machines undersampling xgboost pycharm-ide
Language:Jupyter Notebook 0
MirrasHue / Intro-to-AI
An assignment from my Introduction to Artificial Intelligence course, in which we had to treat the datasets, train some models for classification and adjust their parameters
imblearn pandas python sklearn
Language:Jupyter Notebook 0
pratiksha2712 / Customer-Churn-Analysis-and-Prediction
Data analysis and ML Modelling
eda imblearn jupyter-notebook machine-learning-deployment machine-learning-models pandas-library
Language:Jupyter Notebook 0
Shipra-09 / Project-Vehicle-Insurance
This Github repository contains cross selling of health insurance customers on vehicle insurance product. We have to predict whether a customer would be interested in Vehicle Insurance or not by building a ML model. Exploring Insights/Inferences by performing EDA on the given project data. Finding the high accuracy
accuracy-score confusion-matrix ensemble extra-trees-classifier heatmap imblearn knn-classifier label-encoder logistic-regression matplotlib-pyplot numpy one-hot-encoding pandas random-forest-classifier random-over-sampling seaborn sklearn-library standardscaler
Language:Jupyter Notebook 0
cerenyanik / Heart_Failure_Estimation-ANN
In this Supervised Machine Learning Project, it is aimed to create a model to estimate mortality caused by Heart Failure by using the Artificial Neural Network Model.
artificial-neural-networks imblearn tensorflow sklearn
Language:Jupyter Notebook
egorumaev / 2023-ods-turnstiles
Идентификация посетителя в зависимости от характерного времени его прохода на территорию организации
featureengineering imblearn pandas pipeline python3 sklearn catboost multiclass-classification
Language:Jupyter Notebook
egorumaev / 2023-telekom-customers-churn
Прогнозирование оттока клиентов оператора связи
catboost imblearn lightgbm pandas phik pipeline python3 sklearn xgboost classification
Language:Jupyter Notebook
KarthigaKM / Predicting-Breast-Cancer-in-a-patient
The project includes exploratory data analysis to gain insights into the data, data preprocessing for model preparation, and the use of ensembling techniques like Random Forest and Gradient Boosting for classification.
imblearn matplotlib numpy pandas pil scikitlearn-machine-learning seaborn streamlit
Language:Jupyter Notebook
saikrishnabudi / Random-Forest
Data Science - Random Forest Work
adasyn classification counter featureselection gridsearchcv imbalanceddata imblearn machinelearning pipeline randomforest sklearn-metrics smote smotetomek standardscaler
Language:Jupyter Notebook
xinguanca / MLproject_creditcardfraud
My first machine learning project.
average-precision confusion-matrix correlation-analysis extra-trees-classifier imblearn matplotlib numpy pandas pycaret seaborn sklearn
Language:Jupyter Notebook

imblearn

GenTaylor / Traffic-Accident-Analysis

sharmaroshan / Fraud-Detection-in-Insurace-Claims

pratik-choudhari / Intent-classification-using-python

binaryvexjuiit / Detecting-Facial-Diseases-Through-Neural-Networks

hdkronke / cc-customer-attrition-project

kalyaniasthana / CS273A_project_diabetes

nnilayy / Classification-Notebook

Sanushi-Salgado / Tumor-Teller-Prediction-Module

shayleaschreurs / Machine-Learning-Trading-Bot

spapicchio / Gamma-Telescope-Analysis

AJMnd / Credit_Risk_Analysis

alessandrosocc / Machine-Learning-Project-2022

ChaitanyaC22 / Fraud_Analytics_Credit_Card_Fraud_Detection

clairempr / spooky-classify

cp-PYFOREST / PYFOREST-ML

ImMaxRoss / predicting_churn

NaveenKumarMaurya / datascience-project-portfolio

npantfoerder / credit-risk-analysis

prohogiy90 / ds-model-of-the-behavior-of-the-SberAvtopodpiska-customers

SayamAlt / Fraudulent-Transactions-Prediction

shanuhalli / Assignment-Random-Forest

shinho123 / 23.11.10-1st-Korean-Society-of-Industrial-Engineers

SpaceFrostDev / telco_kaggle

adkwn1 / predict_customer_churn

alaa-aleryani / Credit_Risk_Classification

egorumaev / 2023-cirrhosis-outcomes

jianninapinto / Bandersnatch

MirrasHue / Intro-to-AI

pratiksha2712 / Customer-Churn-Analysis-and-Prediction

Shipra-09 / Project-Vehicle-Insurance

cerenyanik / Heart_Failure_Estimation-ANN

egorumaev / 2023-ods-turnstiles

egorumaev / 2023-telekom-customers-churn

KarthigaKM / Predicting-Breast-Cancer-in-a-patient

saikrishnabudi / Random-Forest

xinguanca / MLproject_creditcardfraud