Synthetic Minority Over-sampling Technique
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Updated
Mar 27, 2017 - Python
Synthetic Minority Over-sampling Technique
Develop predictive models that can determine, given a particular compound, whether it is active (1) or not (0).
Synthetic Minority Over-sampling Technique Implementation
Text classification with scikit-learn, used to make predictions for Kaggle Spooky Author Identification competition
This capstone project was completed for the Winter 2018 Galvanize Data Science Immersive program. The project aid users in rooting out the usage of fake images on the internet by automatically scraping web pages related to a topic of interest, cross referencing the images from each each web page with a directory of known fake images, and identif…
Model with Dimensionality Reduction with performing SMOTE and Tuning will get comparable results comparing with off-the-shelf models in Sentiment Analysis of Citations (Athar 2011).
Data Science Case Study
ICSE'18: Tuning Smote
Dealing with class imbalance problem in machine learning. Synthetic oversampling(SMOTE, ADASYN).
Comparison of FFT, DE_RF against SMOTUNED
HR Analytics Dataset
Performance comparison of classification algorithms
Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.
Awarded 1st position in 'Google-Krenicki Hackathon' for cloud based ML framework to predict US household income for real-estate brokerage firm; using Google Colab and AWS S3
A minority oversampling method for imbalance data set
The experimental codes using PyTorch from the paper that was submitted to GECCO 2020.
The computing scripts associated with our paper entitled "Oversampling Highly Imbalanced Indoor Positioning Data using Deep Generative Models".
Scripts developed for the paper "Understanding when SMOTE works", developed in the "Knowledge Extraction and Machine Learning" (ECAC) class.
Add a description, image, and links to the smote topic page so that developers can more easily learn about it.
To associate your repository with the smote topic, visit your repo's landing page and select "manage topics."