Abstract:
The purpose ofthis project is to compare, contrast and examine naive Bayes, apriori
algorithms and support vector machine for IDS. This project focuses on data mining
concepts and techniques that give meaning to data and classification techniques
which are used in data mining which includes Anomaly detection, Regression,
Association rule learning, Clustering, summarization and regression,
different mining tools to solve the problems. We use some research methods
involving tracking patterns which is used to recognize data patterns in data set.
There are
We used supervised learning in this project because supervised learning uses training
data for inferred function which helps in mapping the new examples. It helps to
identify the class labels ofthe instances which are unseen. It generalizes the training
data from unseen data according to general ways.
