Classification with imbalanced classes

Machine learning model for Credit Card fraud detection

Predict loan approval by using different variable selection methods

A collection of machine learning mini-projects.

Predict whether customers of a bank will subscribe to a term deposit and analyze customer behaviour based on the bank's historical telemarketing campaign records.

Machine Learning model for Credit Card Fraud Detection

Using SageMaker's linear classifier to detect fraud. Addressing class imbalance and setting target metrics for Precision and Recall

Class imbalance correction algorithm for multiple-instance data

Sampling-based class imbalance solutions for multiple-instance classification

PREDICTING A PULSAR STAR - A Classic Class Imbalance Problem

Evaluate Machine Learning Models with Yellowbrick

Most existing classification approaches assume the underlying training set is evenly distributed but many real-world classification problems have an imbalanced class distribution, such as rare disease identification, fraud detection, spam detection, churn prediction, electricity theft & pilferage etc.

A credit card fraud detection kernel

jBVQ: Bayes Vector Quantizer for Java

To deal with the class imbalance problem in multi-label learning with missing labels, we propose Class Imbalance aware Missing labels Multi-label Learning, CIMML. Our proposed method handles class imbalance issue by constructing a label weight matrix with weight estimation guided by how frequently a label is present, absent, and unobserved.

The objective of this analysis is to better understand the characteristics of Detroit Schools with elevated lead levels as identified via testing in 2016 by aggregating three publicly available data sources from the city of Detroit.

Variational Autoencoder based Imbalanced Alzheimer detection using Brain MRI Images

In this project, we will build a text classification model on song lyrics. The task is to predict the artist from a piece of text.

This project harnesses the power of LSTM and Keras, with TensorFlow as the backend, to conduct sentiment analysis on IMDB movie reviews. It effectively categorizes the reviews into positive or negative sentiments, offering valuable insights into the world of text analysis.