arijitiiest / Malaria-Detection

Malaria Detection Project on Malaria Cells

Malaria Detection

Project Overview

• Compare Naive Bayes, SVM, XGBoost, Bagging, AdaBoost, K-NN, etc. for Malaria Cells classification
• Used different feature extraction techniques like HOG, LBP, SIFT, SURF, pixel values
• Feature reduction techniques PCA, LDA
• Normalization techniques such as z-score and min-max
• Classifiers such as Naive Bayes, SVM XGBoost, Bagging, AdaBoost, K-Nearest Neighbors, Random Forests
• Metrics such as Accuracy, Precision, Recall, F1 score, and ROC

Dataset

Infected Cells

Uninfected Cells

Result