Optimizing SVM Regression Prediction Based on Matlab's Cuckoo Search Algorithm
Introduction:
Support Vector Machine (SVM) is a commonly used machine learning algorithm that can be used for regression prediction tasks. Cuckoo Search Algorithm (CSA) is an optimization algorithm based on simulating nest-covering and egg-laying behavior of birds, which has global convergence and high search efficiency. This article will introduce how to use Matlab to write the cuckoo search algorithm to optimize the SVM regression prediction model, and provide the corresponding source code.
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SVM regression prediction
SVM regression is to find an optimal hyperplane, so that the distance between the sample point and the hyperplane is minimized, so as to achieve regression prediction. Specifically, given a training sample set {(x1, y1), (x2, y2), …, (xn, yn)}, where xi is the input feature and yi is the corresponding output value. The goal of SVM regression is to find a linear function f(x) = w x + b such that for all i, |f(xi) - yi| ≤ ε is satisfied, and ε is minimized as much as possible. -
Cuckoo Search Algorithm
Cuckoo Search Algorithm is an optimization algorithm based on the breeding behavior of birds in nature. It realizes the exploration of the search space by simulating the cuckoo egg-laying behavior. The basic idea of the algorithm is to maintain a set of nests (solution space), each nest corresponds to a candidate solution. By simulating the behavior of birds looking for nests and stealing eggs from their nests, information transfer and evolution among candidate solutions are realized. -
Cuckoo search algorithm optimizes SVM regression prediction
3.1 Data preprocessing
First, for a given training data set, data standardization is performed to scale the feature values to an appropriate range. The commonly used method is Z-score standardization, which is to subtract the mean from each feature value and divide it by the standard deviation.
3.2 Cuckoo search algorithm
In the cuckoo search algorithm, each nest corresponds to a candidate solution, that is, a set of SVM modules