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To help enterprises quickly adapt to the environment of green finance, a technology innovation performance prediction method based on machine learning is proposed to improve digital convenience. Firstly, by analyzing scientific and technological innovation, the authors design four characteristics: the number of theses, the quantity and quality of projects, the level of technology transformation, and the value of commercialization. Then, according to the above features, a feature processing method based on improved attention mechanism is proposed to deeply explore the internal relationship between the four features. Finally, a performance evaluation method is used based on the temporal convolution network (TCN) that can predict the performance of scientific and technological innovation by inputting enhanced features. The experiment demonstrates that the proposed method can reach 0.846, 0.869, and 0.851 in terms of the precision, recall, and H value, respectively, which can help enterprises predict the performance and improve the electronic convenience of enterprises.

Research on Enterprise Digital Agility Based on Machine Learning: An Evaluation of Green Financial Technology