ABSTRACT
A Cardiovascular disease which is additionally referred to as heart diseases that have been a common and steady issue in the field of medical research. Nowadays various methods were applied which is not robust for the prediction of human being expenses and disease risks for patients. This paper proposed an Orthogonal Local Preserving Projection (OLPP) method to reduce the function dimension of the input high-dimensional data. The dimension reduction improves the prediction rate with the help of hybrid classifier i.e. Linear Vector Quantization method combine with the Levenberg-Marquardt (LM) training algorithm in the neural network. The combination of LVQ (Learning Vector Quantization) and LM (Levenberg-Marquardt) algorithms is a hybrid approach to solve optimization problems, particularly in pattern recognition and machine learning.LVQ is a supervised learning algorithm that is used to classify data into pre-defined categories. It uses a set of prototype vectors that represent each class and updates the prototypes based on the training data. LM, on the other hand, is a non-linear optimization algorithm that is used to minimize the sum of squared residuals between the model and the data. To combine LVQ and LM, the LVQ algorithm is used to initialize the model parameters, and then the LM algorithm is used to optimize the parameters and it determines the best network parameters such as weights and bias that minimizes the error. This combination results in a hybrid approach that benefits from the strengths of both algorithms and can produce better results than using either algorithm alone. The combination of LVQ and LM has been applied to various pattern recognition and machine learning tasks, such as image classification, speech recognition, and data clustering, among others. The final output of the optimization technique is combined with the performance metrics as accuracy, sensitivity, and specificity. From the result, it is observed that hybrid optimization techniques increase the accuracy of the heart disease prediction system.
