Topic: smote Goto Github
Some thing interesting about smote
Some thing interesting about smote
smote,...............Work in progress................ Flatiron school capstone project. This project uses NLP techniques (TF-IDF, Word Analysis, Bag of Words) to predict the legitimacy of job ads. It features different statistical models such as Naive Bayes, Random Forest and XGBoost and addresses the class imbalance using the SMOTE.
User: aghilissen
smote,ICSE'18: Tuning Smote
Organization: ai-se
Home Page: https://dl.acm.org/citation.cfm?id=3180197
smote,Implementation of SMOTE - Synthetic Minority Over-sampling Technique in SparkML / MLLib
User: alivcor
smote,A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features
Organization: analyticalmindsltd
Home Page: http://smote-variants.readthedocs.io
smote,This repository contains the code of our published work in IEEE JBHI. Our main objective was to demonstrate the feasibility of the use of synthetic data to effectively train Machine Learning algorithms, prooving that it benefits classification performance most of the times.
User: antorguez95
smote,Learn and Explore
User: arunvignesh15
smote,HR Analytics Dataset
User: ashomah
smote,Credit Card Fraud Detection Project
User: ashutosh27ind
smote,A python library for repurposing traditional classification-based resampling techniques for regression tasks
User: atif-hassan
smote,Multi-View LEArning-based data Proliferator (MV-LEAP) for boosting classification using highly imbalanced classes.
User: basiralab
smote,Application fo sentiment analysis using VADER and Support Vector Machine (SVM) with SMOTE
User: bayhaqy
Home Page: https://analisa-sentimen.herokuapp.com
smote,Address imbalance classes in machine learning projects.
User: bhattbhavesh91
smote,My masters thesis where I built a model pipeline using a CNN, SVM, and a custom SMOTE oversampling technique to identify and classify Alzheimer's in brain CT scans.
User: bjhammack
smote,Build and evaluate several machine learning algorithms to predict credit risk.
User: cedoula
smote,Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/
User: damianhorna
smote,Data Science project. ML algorithms to detect voice disorders.
User: desininja
smote,This repository presents the code for digital modulation detection in Communication networks
User: earthat
Home Page: https://free-thesis.com
smote,This repository is for MATLAB code for balancing of multiclass data by SMOTE
User: earthat
Home Page: https://free-thesis.com
smote,Machine-Learning project that uses a variety of credit-related risk factors to predict a potential client's credit risk. Machine Learning models include Logistic Regression, Balanced Random Forest and EasyEnsemble, and a variety of re-sampling techniques are used (Oversampling/SMOTE, Undersampling/Cluster Centroids, and SMOTEENN) to re-sample the data. Evaluation metrics like the accuracy score, classification report and confusion matrix are generated to compare models and determine which suits this particular set of data best.
User: fischlerben
smote,Dealing with class imbalance problem in machine learning. Synthetic oversampling(SMOTE, ADASYN).
User: hk-mp5a3
smote,The experimental codes using PyTorch from the paper that was submitted to GECCO 2020.
User: hwyncho
smote,Machine Learning Telecom Churn Model
User: iici-psiddineni
smote,Apply 7 common Machine Learning Algorithms to detect fraud, while dealing with imbalanced dataset
User: ireneliu521
smote,spark tutorial for big data mining。包括app流量运营分析、als推荐、smote样本采样、RFM客户价值分群、AHP层次分析客户价值得分、手机定位数据商圈挖掘、马尔可夫智能邮件预测、时序预测、关联规则、推荐电影好友等。
User: jiangnanboy
smote,Synthetic Minority Over-sampling Technique
User: kaushalshetty
smote,Detect Fraudulent Credit Card transactions using different Machine Learning models and compare performances
User: laurentveyssier
smote,Analysis and classification using machine learning algorithms on the UCI Default of Credit Card Clients Dataset.
User: matteom95
Home Page: https://archive.ics.uci.edu/dataset/350/default+of+credit+card+clients
smote,Predict the operational status of waterpoints to help the Tanzanian Government provide more clean water to its population using a Machine Learning Classifier
User: merb92
smote,Approx-SMOTE: fast SMOTE for Big Data on Apache Spark
User: mjuez
smote,in this project we used image processing Technique to classify 9 class malwares our final goal is to reach an appropriate model with high accuracy and small size and computational cost
User: mohammadreza-babaeimosleh
smote,Colab Compatible FastAI notebooks for NLP and Computer Vision Datasets
User: navneetkrc
smote,Synthetic Minority Over-Sampling Technique for Regression
User: nickkunz
Home Page: https://pypi.org/project/smogn
smote,A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.
User: nive927
smote,Implementation of the Geometric SMOTE over-sampling algorithm.
Organization: nova-ims-innovation-and-analytics-lab
Home Page: https://nova-ims-innovation-and-analytics-lab.github.io/geometric-smote/
smote,Classifying whether the credit card transaction is fraudulent or not using Logistic Regression
User: prabhatk579
smote,Classifying whether the credit card transaction is fraudulent or not using Support Vector Machines
User: prabhatk579
smote,An implementation of SMOTE
User: rikhuijzer
Home Page: https://rikhuijzer.github.io/Resample.jl/
smote,Advancing Cybersecurity with AI: This project fortifies phishing defense using cutting-edge models, trained on a diverse dataset of 737,000 URLs. It was the final project for the AI for Cybersecurity course in my Master's at uOttawa in 2023.
User: rimtouny
smote,Data mining with Go.
User: shulhan
smote,Predicting the severity of accident
User: sonnguyen129
Home Page: https://traffic-severity-prediction.herokuapp.com/
smote,A repository of resources for understanding the concepts of machine learning/deep learning.
User: sudhakarkuma
smote,Identifying fraudulent credit card transactions in a highly imbalanced dataset by oversampling and using ensemble learning/neural network
User: sunnyks
smote,The machine learning project on UCI imbalanced data.
User: swordspoet
smote,Which one of five German authors can text be attributed to?
User: taylorhawks
smote,Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.
User: tgsmith61591
smote,Analysis and preprocessing of the kdd cup 99 dataset using python and scikit-learn
User: timeamagyar
smote,Bank customers churn dashboard with predictions from several machine learning models.
User: zunicd
Home Page: https://bank-churn-predictions.onrender.com
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