A new method called AMCMRP-Outlier was developed to quickly detect unusual data points in small datasets by considering specific constraints. By using a matrix structure to find rare patterns that meet the constraints, the method efficiently identifies outliers based on their deviation from normal data. Experiments showed that AMCMRP-Outlier accurately detects outliers in less time compared to existing methods, improving the reliability of data streams.