Pancreatic cancer classification using logistic regression and random forest

<span id="docs-internal-guid-2f1ba81b-7fff-8c46-5600-cbb159235091"><span>In the medical field, technology machinery is needed to solve several classification problems. Therefore, this research useful problem of field by using machine learning. This study discusses pancreatic cancer regression logistics and random forest. By comparing accuracy, precision, recall (sensitivity), F1-score both methods, then we will know which method better in classifying dataset that get from Al-Islam Hospital, Bandung, Indonesia. The results showed forest has accuracy than logistic regressions. It can be seen with maximum regressions 96.48 30% data training 99.38% 20% training.</span></span>