Searches for generic transient (burst) gravitational waves must efficiently scan a broad parameter space while minimising the impact of spurious transient noise. The coherent WaveBurst (cWB) algorithm is a wavelet-based time-frequency analysis developed for gravitational wave event identification with minimal assumptions of the signal waveform. An overview of cWB will be presented including the process of coherently combining data from multiple detectors by taking into account the directional sensitivity (antenna patterns) of all detectors in the network. Recent sensitivity enhancements through the use of multivariate (machine learning) methods will be reviewed with particular description of application of Gaussian Mixture Model approach. Specific tunings for gravitational wave signals from parabolic black hole capture events as well as some applications beyond gravitational waves will also be discussed.