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kochlisGit / Wine-Preference-Analysis

Star 2

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.

python data-science machine-learning neural-network chemistry tensorflow scikit-learn keras hyperparameter-optimization data-analysis wine hyperparameter-tuning interpretability regression-analysis feature-importance optuna regression-model wine-analysis physicochemical-properties shap-values
  • Updated Jul 17, 2022
  • Jupyter Notebook

sachin17git / Malware-detection-ML

Star 3

Android malware detection using machine learning.

python machine-learning random-forest machine-learning-algorithms feature-selection logistic-regression bayesian-inference support-vector-machines bayesian-optimization multicollinearity k-nearest-neighbours malware-detection voting-classifier shapley-values xgboost-classifier shap-values shapley-additive-explanations catboost-classifier stacking-classifier
  • Updated Nov 23, 2022
  • Jupyter Notebook

sanketsanap5 / Bank-Loan-Status-Predictive-Analysis

Star 0

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 …

visualization python machine-learning machine-learning-algorithms pandas seaborn feature-selection predictive-modeling automl model-interpretability shap-values
  • Updated May 10, 2022
  • Jupyter Notebook

gyepescalero / TFM

Star 0

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.

machine-learning deep-neural-networks deep-learning artificial-intelligence explainable-ai explainable-ml explainability shap-values
  • Updated Jan 3, 2021
  • Jupyter Notebook

haghish / shapley

Star 9

Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles

machine-learning machine-learning-algorithms feature-selection feature-extraction class-imbalance shapely feature-importance shap shapley-decomposition shapley-value shapley-values shap-values shapley-additive-explanations shap-analysis class-imbalance-problem shapleyvalue weighted-shapley weighted-shap weighted-shap-confidence-interval weighted-shapley-ci
  • Updated May 8, 2024
  • R

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