This study investigates whether machine learning algorithms can be used to accurately classify tempo into two classes based only on the musical note sequence written on musical scores. Herein, the tempo that is manually estimated by looking at the score is simulated via Kansei (emotional) information processing. The tempo threshold was set at d = 120. Results showed that even after successful learning, the algorithms showed low recognition rates while classifying slow tempo class from the evaluation data and some data were erroneously recognized. In contrast, the algorithms showed high recognition rates when classifying fast tempo class from the evaluation data. The algorithms did not show any recognition error in the data.