There are 0 repository under shap-values topic.
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
In this project, I have utilized survival analysis models to see how the likelihood of the customer churn changes over time and to calculate customer LTV. I have also implemented the Random Forest model to predict if a customer is going to churn and deployed a model using the flask web app.
A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc
In this project, we have to create a predictive model which allows the company to maximize the profit of the next marketing campaign
🐍 Mental Maps Related to Contents in Data Science 🐍
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Android malware detection using machine learning.
The purpose of this work is the modeling of the wine preferences by physicochemical properties. Such model is useful to support the oenologist wine tasting evaluations, improve and speed-up the wine production. A Neural Network was trained using Tensorflow, which was later tuned in order to achieve high-accuracy quality predictions.
Prediction if patients with symptoms have COVID-19 based on clinical variables (blood related variables, urine related variables, age, etc)
WiDS Datathon 2020 on patient health through data from MIT’s GOSSIS (Global Open Source Severity of Illness Score) initiative.
Github Repository for the paper "Different Algorithms (Might) Uncover Different Patterns: A Brain-Age Prediction Case Study" - BIBM 2023
This project was developed during the course Laboratory of Computational Physics
Generate predictive model using supervised learning method to enhanced coupon acceptance rate using python.
Experimenting with SHAP values to explain how a given Machine Learning model works.
Explainable Landscape-Aware Optimization Performance Prediction
Repo for Manzano Analytics HTML website
Jantahack : BigMart Sales Prediction using LGBM Regressor and Model interpretation using SHAP
XAI analytics to understand the working of SHAP values and applying it to the breast cancer dataset to get the explanation behind the predictions made.
XAI analytics to understand the working of SHAP values
Predicción del precio de venta de las viviendas en venta y de las viviendas en alquiler de Barcelona.
ML-solution of the case of the District hackathon Leaders of Digital 2023. The task was to predict accidents (accidents, pipe ruptures, fires) based on the weather forecast for each of the urban districts. Gradient boosting (macro f1), cross-validation, shap values.
Análisis de modelos de Deep Learning mediante SHAP values. Desarrollo y programación de herramientas que permitan interpretar modelos de Deep Learning usando las SHAP values, generando una mejor explicación de los factores en los que se basa el modelo a la hora de tomar sus predicciones.
Modelo de boosting que a partir de los datos del usuario de una fintech predice si activaría la tarjeta de debito que ofrece la misma empresa, y en cuantos dias lo haría
:honeybee: Materials and homework assignments for HSE recommender systems course
Financial distress prediction from Kaggle
erformed a predictive analysis on the customer's Bank Loan Application data to predict loan status. Using python, pandas, scipy, seaborn, AutoML libraries, and machine learning techniques. Used Machine Learning techniques to accurately predict the evaluation scheme if the particular loan will be 'Fully Paid' or 'Charged Off'. This means if Bank accepts a particular person's loan application will it be 'Fully Paid' or 'Charged Off'
Loan-Default-Prediction