Scoring rules like the Brier Score (Mean Squared Error, Quadratic Score) and Log Loss (Cross-Entropy, Negative Log-Likelihood, Logarithmic Score) can favor incorrect predictions. To address this limitation, the Probabilistic Brier Score (PBS) and Probabilistic Logarithmic Loss (PLL) have been introduced for probabilistic classifiers.

Personalized Cancer Diagnosis is a tool that predicts the effect of genetic mutations in cancer patients. Given a gene, its variation, and clinical text, it uses advanced machine learning (Logistic Regression with TF-IDF features) to classify mutations into 9 categories.

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This project provided practice with logistic regression and the cost functions MSE and log loss

Machine Learning algorithms implemented from scratch

This project focuses on implementing and analyzing the learning process in decision trees using Connect 4.

Customer Churn Prediction using Logistic Regression and CatBoost

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Alvin Smart Money Management Classification Challenge

Predicting Animal Shelter Outcomes Using Ensemble Learning

Identify duplicate pair of questions to save readers and writers time on Quora

Machine Learning - Binary Classification

Logistic Regression example on MNIST dataset