Breast Histopathology Image Classification: A Comparative Evaluation of SVM, Random Forest and CNN

Artificial intelligence (AI) uses the impressions of human intelligence to wire machines to think and mimic the human behaviour. Deep Learning, Machine Learning, Neural Networks, are a few concepts included in AI among many others. Convolutional neural network (ConvNet or CNN) is a category of machine learning commonly applied for image recognition and processing pixel data. Support Vector Machine (SVM) algorithm is a Supervised Learning algorithm used often for Regression problems and Classification problems. Random Forest is a collaborative algorithm which is also used for both Regression and Classification problems. This paper provides a comparative analysis of CNN, SVM and Random Forest Algorithms. The dataset used is the Breast Histopathology Image Dataset.