Decision Trees by Pattern Recognition, classification on a dataset of breast cancer
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Updated
May 16, 2020 - MATLAB
Decision Trees by Pattern Recognition, classification on a dataset of breast cancer
Breast cancer detection with screening mammograms obtained from regular screening.
This repository contains a pre-trained image classification model utilizing the VGG16, VGG19 and EfficientNet-B7 architecture. The model supports transfer learning and fine-tuning, offering flexibility for adapting to specific image recognition tasks.
Principal_Component_Analysis
Tensorflow 2.0 and Keras Regression and Classification including TensorBoard.
A machine learning project which predicts the healthcare based on given certain features.
Classification of Breast Cancer diagnosis Using Support Vector Machines
Small project to accurately predict nature of a tumour (benign/malignant) using the UCI Wisconsin breast cancer dataset (https://www.kaggle.com/uciml/breast-cancer-wisconsin-data)
Breast cancer detection using machine learning with deployment of model
Unsupervised clustering of transcriptomic and proteomic data for breast cancer patients
Breast Cancer Classification ( SVM Implementation)
Projects on Neural Networks for Breast Cell Classification - Machine Learning (MEng), supervised by Prof. C. Sansone and Eng. M. Gravina(2024)
Breast cancer detection using machine learning classification is a project where you build a model to identify whether a given set of medical features indicates the presence of breast cancer. This project involves using a labeled dataset of medical records, where each record is classified as either indicating breast cancer or not.
Breast cancer classifier using Logistic regression, SVC, K-NN, and Random Forest Classification
Development and testing of various models for classification of Breast Cancer and Cancer Recurrence from human extracellular RNA transcripts. Final Project for CSE 283: Data Wrangling in Bioinformatics
This is about to check the category of breast cancer either M type or B type.
Built a machine learning model for Breast Cancer Classification using "Breast Cancer Wisconsin (Original) Data Set". I used various Machine learining models, the best accuracy was 96% with 9% log loss using Neural Networks.
logistic regression from scratch using python to solve binary classification problem using breast cancer dataset from scikit-learn. A complete breakdown of logistic regression algorithm.
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