Controlled electrical discharge aids in conditioning of the system while uncontrolled discharges damage its electronic components. DC Accelerator being a high voltage system is no exception. It is useful to classify electrical discharges according to the severity. Experimental prototypes of the accelerator discharges are developed. Photomultiplier Tubes (PMTs) are used to detect the signals from these discharges. Time and Frequency domain characteristics of the detected discharges are used to extract features. Machine Learning approaches like Fuzzy Logic, Neural Network and Least Squares Support Vector Machine (LSSVM) are employed to classify the discharges. This aids in detecting the severity of the discharges.