KDD 99 intrusion detection datasets, which are based on DARPA 98 dataset, provides labeled data for researchers working in the field of intrusion detection and is the only labeled dataset publicly available. Numerous researchers employed the datasets in KDD 99 intrusion detection competition to study the utilization of machine learning for intrusion detection and reported detection rates up to 91% with false positive rates less than 1%. To substantiate the performance of machine learning based detectors that are trained on KDD 99 training data; we investigate the relevance of each feature in KDD 99 intrusion detection datasets. To this end, information gain is employed to determine the most discriminating features for each class.