The Construction of Psychological Intervention Mechanism of Deep Learning in the Prevention of Legal Anomie

The convenience of big data processing technology has played a great advantage in many scenarios, and its deep learning can effectively mine different types of data in data sets. Applying this method to mining psychological prediction data set of legal anomie behavior can effectively prevent the occurrence of illegal behavior. The effective analysis of its psychological characteristics and the changes of psychological emotions will have hidden dangers, so it is necessary to extract this kind of data in such cases. Therefore, the forest algorithm under deep learning uses weight factors, simple sampling, and other ideas to build the intervention mechanism, which will improve psychological quality to prevent anomie. The experimental results of this paper are as follows: (1) In the case of testing psychological fluctuation by three algorithms, the forest algorithm calculates the psychological change area steadily, with the increase of the number of samples. (2) In the data sample extraction of different dimensions, the test value increases with the increase of dimensions, and it is stable at 12 dimensions. (3) Preventive intervention is extremely important to construct the mechanism before the anomie behavior occurs, and the longest running time of the roll neural network is as much as 950 s. (4) The data mining technology for constructing the intervention mechanism accounts for 15.4% of counseling, which also shows that the auxiliary measures for preventing behavior are particularly important.