Machine learning classifier for cancer tissues 🔬

Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. In this project, certain classification methods such as K-nearest neighbors (K-NN) and Support Vector Machine (SVM) which is a supervised learning method to detect breast cancer are used.

simple tutorial on Machine Learning with Scikitlearn

Implementation of SVM Classifier To Perform Classification on the dataset of Breast Cancer Wisconin; to predict if the tumor is cancer or not.

breast cancer feature selection using binary particle swarm optimization

This project is to test classification algorithms wrote from scratch in python using only numpy. Algorithms wrote in this project: KNN, Logistic Regression and Naive Bayes classifier.

This analysis aims to observe which features are most helpful in predicting malignant or benign cancer and to see general trends that may aid us in model selection and hyper parameter selection.

Here I tried various Machine Learning algorithms on different cancer's dataset present in CSV format.

Breast Cancer Wisconsin (Diagnostic) Prediction Using Various Architecture, though XgBoost Classifier out performed all

Using the Knn algorithm, it detects whether the tumor is benign or malignant in people diagnosed with breast cancer.

This project is a part of research on Breast Cancer Diagnosis with Machine Learning algorithm using data-driven approaches. The final outcomes of the research were later published at an IEEE Conference and added to IEEE Xplore Digital Library.

Classifying breast cancer using knn, svm , naive bayes and decision trees on Matlab

Breast Cancer Prediction Web API

Python feed-forward neural network to predict breast cancer. Trained using stochastic gradient descent in combination with backpropagation.

Breast Cancer Detection

In this machine learning project I will work on the Wisconsin Breast Cancer Dataset that comes with scikit-learn. I will train a few algorithms and evaluate their performance. I will use ipython (Jupyter).

Flyweight data mining with R

Breast cancer diagnoses with four different machine learning classifiers (SVM, LR, KNN, and EC) by utilizing data exploratory techniques (DET) at Wisconsin Diagnostic Breast Cancer (WDBC) and Breast Cancer Coimbra Dataset (BCCD).

about breast cancer data's feature selection method (breast cancer wisconsin)

Analysing and predicting wheter the cancer is benign or malignant using machine learning models.

Make predictions for breast cancer, malignant or benign using the Breast Cancer data set

Prediction of Benign or Malignant Cancer Tumors

K means clustering for breast-cancer-wisconsin.data from scratch

Artificial Neural Network - Wisconsin Breast Cancer Detection

Breast Cancer Diagnosis and Prognosis Estimatior Using TPOT

The aim of the project, to determine whether the breast cancer cell is malignant or benign.I got the dataset from Kaggle.

The objective of the project was to build various models and compare their prediction performance based on accuracy.

Prediction of Breast Cancer using Logistic Regression/Decision Trees/Boosted Decision Trees

This repository is for the work I did in machine learning using Python.

Prediction of breast cancer using Random Forest Classification on the Wisconsin Breast Cancer Dataset. Implemented with Streamlit.