Research Article
A Multiple Kernel Learning Approach for Air Quality Prediction
Input: dataset: , n samples | Output: decision function of MKSVC | Start First, get the kernel coefficients by optimizing the single kernel-base learners () | Second, get the weight of each kernel by the centered kernel alignment algorithm () | Third, get the number of kernels by boosting approach (P) | Fourth, get the combined optimized kernel | Then, use SVC as the base learner and optimize it with a general optimizing algorithm | Return | Stop |
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