The Effect of Prediction on Employee Engagement Organizational Commitment and Employee Performance Using Denoised Auto Encoder and SVM Based Model

The purpose of human resources is to ensure that the appropriate people are hired for open positions at appropriate times, that the system receive the necessary training, and that their performance is monitored and their perspective skills are secure through the use of evaluation methods. Despite the importance of this data to decision-makers, it can be difficult to glean useful insights from large datasets. Data mining has made it possible for human resources experts to automate the hitherto tedious task of manually processing enormous data sets. Finding almost perfect outcomes is the main goal of data mining, which is to discover hidden knowledge in data patterns and trends. The proposed method goes as follows: preprocessing is done by data cleaning and data normalization, feature selection using correlation and information theoretic ranking criteria. The last step in training and evaluating the model is using AE-SVM, which stands for Auto Encoder Support Vector Machine. The suggested model is more effective and performs better than two existing models: Support Vector Machine and AE-CNN. The suggested approach attains an accuracy rate of 94%.