achen353 / Multiclass-Tumor-Classification

Multiclass tumor classification on processed tabular data using one-vs-one logistic regression classifiers

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Multiclass Tumor Classification Using One-vs-one Classifiers

This project aims to classify 5 different classes of tumors based on cleaned tabular data with 800+ features. Given the few samples for each class, I trained a logistic regression classifier for each pair of classes (e.g. 1 classifier to classify if a given data point is more likely to be Class 1 or Class 2) and adopted Learning Valued Preference for Classification (LVPC), a voting strategy that considers the score matrix as a fuzzy preference relation, to aggregate the result.

All the codes are written in Python using Pandas, Numpy, Matplotlib and Scikit-learn libraries.

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Multiclass tumor classification on processed tabular data using one-vs-one logistic regression classifiers


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