Abstract: Peculiarity factor is an important concept in the peculiarity-oriented mining, but its computation is too complex. Using sampling-based method to define the peculiarity factors called sampled peculiarity factor (SPF) can improve operational efficiency without affecting the accuracy. To improve the efficiency of anomaly detection algorithm based on the SPF, learning sampling frequency algorithm was proposed. Combined the optimal sampling frequency and SPF, rcaltime anomaly detection algorithm was proposed. Experiments use real data sets, take confidence as 95 0 o，and the optimal sampling frequency sequence is between 1/32 and 1/16. Simulation results show that false detection rate of the algorithm is 2%.

Key words: Sample peculiarity factor(SPF)，Sampling frequency, Real-time, Anomaly detection