Predicting probability of default (at 12 months from observation) for small companies

This project aims to analyze and model the information retrieved by a real-world IoT system in order to understand which are the relationships in the dataset chosen between the dependent variables and the selected target feature. To help the understanding of the inner working of the models adopted, several machine learning interpretability techn…

Just a lib converting HCI communication dumps to Cypress chips into LiME memory dumps. !!! Migrated to Codeberg 🏔️ !!!

Bengali Misogyny Identification with Deep Learning and LIME.

client subsection to a term deposit

🍋💎 Ruby Lime macro interpreter

Cardiovasular Disease Detection using Naive Bayes, Logistic Regression, Random Forest & Support Vector Machine, while comparing the Naive Bayes models with the rest. LIME was also used to explain the predictions of the model.

Tasks for Advanced Machine Learning Technologies Course @ ITMO University.

Credit Scoring from inputs to interpretation, see Streamlit_app repo to get to the dashboard

Tasks for Advanced Machine Learning Technologies Course at ITMO University.

A solid foundational understanding of XAI, primarily emphasizing how XAI methodologies can expose latent biases in datasets and reveal valuable insights.

XAI를 활용한 서울 카페 리뷰 분석

Covid Detection via CT Scan Image Analysis

Contrastive Learning for API Aspect Analysis

This study aimed to assess whether machine learning algorithms would outperform traditional modeling in developing a cesarean delivery prediction model among gravidas with morbid obesity (body mass index of ≥40 kg/m2) to determine whether a primary cesarean delivery may be beneficial.

Multi-classification of ocular diseases using ODIR-5K and uses explainable AI methods to improve the transparency of computer aided diagnostic systems.

qssi-user 11 RKQ1.201004.002 V12.5.5.0.RJQTRXM release-keys