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

breast cancer feature selection using binary particle swarm optimization

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

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.

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

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

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.

Breast Cancer Prediction Web API

Flyweight data mining with R

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

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

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

Breast Cancer Detection

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

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).

Prediction of Benign or Malignant Cancer Tumors