oversampling-technique

There are 0 repository under oversampling-technique topic.

MatteoM95 / Default-of-Credit-Card-Clients-Dataset-Analisys
Analysis and classification using machine learning algorithms on the UCI Default of Credit Card Clients Dataset.
gridsearchcv logistic-regression machine-learning random-forest-classifier oversampling-technique pca-analysis smote svm-classifier decision-trees oversampling undersampling exploratory-data-analysis uci-dataset
Language:HTML 14
shiranzada / pure-noise
Official implementation for "Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images" https://arxiv.org/abs/2112.08810
augmentations batch-normalization deep-learning gaussian-noise imbalanced-data low-data-regime machine-learning normalization-techniques oversampling-technique
14
multilabel-oversampling
phiyodr / multilabel-oversampling
Many algorithms for imbalanced data support binary and multiclass classification only. This approach is made for mulit-label classification (aka multi-target classification). :sunflower:
imbalanced-classification imbalanced-data oversampling oversampling-algorithms oversampling-technique upsampling
Language:Python 10
ramtiin / Credit-Card-Fraud-Detection
In this project, I explore different methods for detecting credit card fraud transactions; including using the Catboost algorithm with undersampling & oversampling methods, and using an almost new approach, by using deep learning and autoencoder.
anomaly-detection deep-learning catboost imbalanced-data credit-card-fraud autoencoders autoencoder oversampling-technique undersampling-technique
Language:Jupyter Notebook 6
jincy-p-janardhanan / imbalanced-fraud-detection
This notebook tries to make fraud/not fraud predictions on a transactions dataset with highly imbalanced data.
machine-learning classification fraud-detection fraudulent-transactions imbalanced-data xgboost smote oversampling-technique
Language:Jupyter Notebook 4
yourssincerely / eurovision
This project provides a comprehensive analysis of the Eurovision Song Contest, with insights derived from both traditional statistical methods and machine learning techniques.
eurovision-song-contest logistic-regression matplotlib-pyplot oversampling-technique prediction-model random-forest scikit-learn smote-sampling sqlalchemy-python tensorflow neural-network
Language:Jupyter Notebook 4
AI-14 / lumpy-skin-disease-classification
Binary classification of lumpy skin disease (imbalanced dataset) using ML algorithms in addition to oversampling/undersampling techniques.
imbalanced-dataset machine-learning oversampling-technique python sklearn smote-sampling undersampling-technique
Language:Jupyter Notebook 2
kumaranurag7 / Job-Reviews-Analysis-Prediction
Data from a website that provides job reviews. The website wants to analyze texts and the corresponding rating that is provided by the user about startups. Based on the texts, try to verify if it corresponds to the score provided by the reviewer. the task helps the website to rank user's reviews or ratings
multiclass-classification oversampling-technique stacking-ensemble word2vec nltk
Language:Jupyter Notebook 2
aabritidutta / Creditcard-Fraud-Detection
Predict if a transaction is a fraud transaction or not, also, dealing with unbalanced data and finding the pattern using correlation between the features.
unbalanced-data undersampling oversampling undersampling-technique oversampling-technique gridsearchcv classification
Language:Jupyter Notebook 1
BibhuPrasadPanda97 / Credit-Card-Default-Risk---AmExpert-CodeLab
Competition conducted by American Express on HackerEarth Platform to Predict Credit Card Defaulters by building Machine Learning Models for the given data.
machine-learning model-building logistic-regression random-forest deep-neural-networks xgboost-model eda analysis visualization outlier-detection imputation-methods oversampling-technique smote-sampling testing predictive-modeling predictive-analytics
Language:Jupyter Notebook 1
Demon-2-Angel / Cereberal-Stroke-Analysis
Cerebral stroke, a critical condition, demands vigilant analysis. Machine learning models, coupled with resampling techniques like SMOTEENN, enhance stroke prediction accuracy by addressing imbalanced datasets.
brain-stroke-analysis-and-classification cerebral machine-learning-algorithms oversampling-technique undersampling-technique
Language:Jupyter Notebook 1
mdabbous88 / Credit_Risk_Analysis
Assess credit risk of applicants using supervised machine learning. Several different machine learning techniques such as SMOTE, SMOTEENN, RANDOM FOREST, EASY ENSEMBLE were applied, the models were assessed using accuracy score, precision and accuracy to choose the best technique that applies to this type of problem.
machine-learning supervised-machine-learning accuracy precision credit-risk smoteenn smoteen random-forest-classifier oversampling-technique undersampling-technique
Language:Jupyter Notebook 1
sailyshah / Credit-card-fraud-detection
Detect potential frauds so that customers are not wrongly charged for items that they did not purchase.
credit-card-fraud hyperparameter-tuning oversampling-technique undersampling-technique adasyn-sampling smote-sampling optimal-threshold roc-curve
Language:Jupyter Notebook 1
Sophy8281 / sms-spam-detection
Spam messages detection model
data-exploration data-visualization data-preprocessing classification oversampling-technique undersampling-technique
Language:Jupyter Notebook 1
sprcoder / Customer_Segmentation_ML
A machine learning project to predict Customers/Clients into correct segment to provide promotional information or for product advertising.
classification clustering decision-tree-classifier k-prototypes machine-learning oversampling-technique random-sampling sklearn-library normalization numpy
Language:Jupyter Notebook 1
abidor13 / linear_regression_salary
There are a number of classification algorithms that can be used to determine loan elgibility. Some algorithms run better than others. We built a loan approver using different Supervised Machine Learning algorithms and compared their accuracies and performances
machine-learning ml decision-trees numpy oversampling-technique pandas sklearn smote smoteenn undersampling
Language:Jupyter Notebook 0
anushaghimire / Credit_Risk_Analysis
credit-risk-analysis machine-learning oversampling-technique undersampling
Language:Jupyter Notebook 0
Arvindhh931 / SMS-Spam-Classification
imbalanced-data oversampling-technique smote spam-classification tfidf-vectorizer text-processing
Language:Jupyter Notebook 0
Emeraldugbeyide93 / Undersampling-and-Oversampling-techniques-for-imbalanced-datasets
Beginner friendly project focusing on dataset imbalances using the oversampling and under sampling techniques
beginner-friendly data-exploration exploratory-data-analysis jupyter-notebook matplotlib-pyplot numpy oversampling-technique pandas python3 seaborn undersampling-technique imblearn
0
gabrielecola / Imbalance_classification_problem
bsc-thesis cost-sensitive-classification oversampling-technique undersampling-technique
Language:TeX 0
Godson199 / Ecological-Footprint-Predictor
In this project, I worked on a classification problem using an imbalanced dataset which predicts ecological footprints. The aim of the project was not necessarily to build a classification model but to investigate the different methods of correcting an imbalanced dataset in order not to build a biased classifier
data-preprocessing data-science data-visualization data-wrangling lgbmclassifier machine-learning oversampling-technique randomforestclassifier smote undersampling-technique xgboost
Language:Jupyter Notebook 0
joshyaffee / healthcare_stroke_ML
Project for predicting strokes from healthcare data for INDE 577 (Spr. 23) at Rice University
data-science data-visualization ensemble-learning healthcare logistic-regression machine-learning neural-networks optimization oversampling-technique python random-forest
Language:Jupyter Notebook 0
nafisa-samia / Credit-Card-Fraud-Detection-Dealing-with-Imbalanced-Data
This project is based on supervised machine learning where you will be predicting whether a credit card transaction is original transaction or fraud transaction based on various parameters. This is a classification problem.
classification-model imbalanced-data machine-learning oversampling-technique undersampling-technique
Language:Jupyter Notebook 0
Naveen-Gowda-2525 / spam-sms-classification
It is a NLP project.The business objective was to predict whether the message is a spam or a ham.
nlp-machine-learning naive-bayes-classifier oversampling-technique exploratory-data-analysis datapreprocessing flask heroku
Language:Jupyter Notebook 0
prankur16shukla / Credit_Card_Fraud_Detection
In this Classification Machine Learning Project, we will be analysing the dataset taken from www.kaggle.com related to details of credit card owners. This data consists of features like Gender, Income type, House type, marital status and many more. Our focus will be on analysing the data, getting the insights related to these features and there role in affecting the target, we will perform feature engineering, feature selection and develop a Classification model that will predict whether it is a Fraud or not based on the new data.
numpy pandas exploratory-data-analysis knn-classifier oversampling-technique matplotlib-pyplot seaborn-plots minmaxscalar sklearn-library
Language:Jupyter Notebook 0
vicaaa12 / advanced-machine-learning
Advanced Machine Learning
adaboost-classifier bagging-classifier confusion-matrix correlation-matrix data-preprocessing ensemble-learning exploratory-data-analysis feature-importance gradientboostinclassifier hyperparameter-tuning missing-value-imputation model-comparison model-performance-comparison outlier-detection oversampling-technique randomforest-classification randomsearchcv undersampling-technique xgboost-classifier
Language:Jupyter Notebook 0
kaggle_fraud_detection
yujansaya / kaggle_fraud_detection
Credit Card Fraud Detection
catboost convolutional-neural-networks feature-scaling imbalanced-data linear-regression neural-network oversampling-technique smote-sampling tomek-link-elimination undersampling xgboost
Language:Jupyter Notebook 0
zaha2020 / Machine_Learning
Machine Learning projects
machine-learning ml classification-algorithm cleaning-dataset machine-learning-algorithms machinelearning-python oversampling-technique pca pca-analysis preprocessing-data svm-model
Language:Jupyter Notebook 0
zonaj2 / credit-risk-classification
An assessment of logistic regression model performance in predicting customer loan worthiness using loan size, interest rate, borrower income, debt-to-income ratio, number of credit accounts, derogatory marks, and total debt as predictive factors.
logistic-regression machine-learning oversampling-technique
Language:Jupyter Notebook 0
aakashsyadav1999 / leed_predictor
The LEED Predictor project is designed to forecast the likelihood of buildings achieving LEED (Leadership in Energy and Environmental Design)
flask-application pipelines random-forest-classifier sklearn oversampling-technique end-to-end machine-learning-algorithms predictive-modeling
Language:Jupyter Notebook
abis330 / footbalysis
Player Rating System in Soccer using Machine Learning
machine-learning oversampling-technique smote-sampling data-science
AfonsoPaula / Apis-Melifera-Honeybee
Prediction of occurrences of a bee species in the Iberian Peninsula 🐝
dataset machine-learning-algorithms numpy oversampling-technique pandas undersampling-technique
Language:Jupyter Notebook
alfianhid / Sentiment-Analysis-of-Mobile-App-Reviews-using-NBC-and-Text-Associations-Case-Study-PLN-Mobile-App
sentiment-analysis sentiment-classification naive-bayes-classifier association-analysis oversampling-technique web-scraping
Language:Jupyter Notebook
aolayeye / Credit_Risk_Analysis
Predicting Credit Risk with undersampling, oversampling, and ensemble methods across various machine learning algorithms.
machine-learning random-forest logistic-regression undersampling-technique oversampling-technique
Language:Jupyter Notebook
ClJuRo / Classification-of-Good-Loans-and-Bad-Loans-using-ML-algorithms
Predictive Modeling of Credit Risk Faced by a P2P lending platform
bagging-ensemble decision-trees logistic-regression machine-learning oversampling-technique random-forest undersampling-technique
Language:Jupyter Notebook
TheThugnomist / BankFraud
Building a machine learning model to check bank frauds
deep-learning keras machine-learning oversampling-technique scikit-learn tensorflow undersampling-technique
Language:Jupyter Notebook

oversampling-technique

MatteoM95 / Default-of-Credit-Card-Clients-Dataset-Analisys

shiranzada / pure-noise

phiyodr / multilabel-oversampling

ramtiin / Credit-Card-Fraud-Detection

jincy-p-janardhanan / imbalanced-fraud-detection

yourssincerely / eurovision

AI-14 / lumpy-skin-disease-classification

kumaranurag7 / Job-Reviews-Analysis-Prediction

aabritidutta / Creditcard-Fraud-Detection

BibhuPrasadPanda97 / Credit-Card-Default-Risk---AmExpert-CodeLab

Demon-2-Angel / Cereberal-Stroke-Analysis

mdabbous88 / Credit_Risk_Analysis

sailyshah / Credit-card-fraud-detection

Sophy8281 / sms-spam-detection

sprcoder / Customer_Segmentation_ML

abidor13 / linear_regression_salary

anushaghimire / Credit_Risk_Analysis

Arvindhh931 / SMS-Spam-Classification

Emeraldugbeyide93 / Undersampling-and-Oversampling-techniques-for-imbalanced-datasets

gabrielecola / Imbalance_classification_problem

Godson199 / Ecological-Footprint-Predictor

joshyaffee / healthcare_stroke_ML

nafisa-samia / Credit-Card-Fraud-Detection-Dealing-with-Imbalanced-Data

Naveen-Gowda-2525 / spam-sms-classification

prankur16shukla / Credit_Card_Fraud_Detection

vicaaa12 / advanced-machine-learning

yujansaya / kaggle_fraud_detection

zaha2020 / Machine_Learning

zonaj2 / credit-risk-classification

aakashsyadav1999 / leed_predictor

abis330 / footbalysis

AfonsoPaula / Apis-Melifera-Honeybee

alfianhid / Sentiment-Analysis-of-Mobile-App-Reviews-using-NBC-and-Text-Associations-Case-Study-PLN-Mobile-App

aolayeye / Credit_Risk_Analysis

ClJuRo / Classification-of-Good-Loans-and-Bad-Loans-using-ML-algorithms

TheThugnomist / BankFraud