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To evaluate military software obsolescence scientifically and systematically, the model of software obsolescence evaluation based on machine learning is pointed. Firstly, the machine learning preprocessing and scaling techniques are used to process the related feature data, then the principal component analysis model is used to extract feature and reduce dimension, eliminate the noise value in the feature data and select important military software obsolete feature data, use particle swarm optimization algorithm to optimize support vector machine parameters and build SVM classification and evaluation model, use confusion matrix accuracy to evaluate the machine model, finally the example verify the model is effective, applicable, and scientific.