The invention discloses a multi-dimensional training method and device for a
support vector machine,
electronic equipment and a computer readable storage medium, and the method comprises the steps: carrying out the
discretization of a training sample
data set, and obtaining a discretized
data set, the discretized
data set comprises a plurality of different attributes, and each attribute corresponds to a plurality of feature vectors; calculating a classification contribution parameter of each attribute
feature vector to obtain a plurality of classification contribution parameters; performing
data mapping on the plurality of classification contribution degrees by using a kernel function to obtain a target function; and optimizing and training the objective function by using a
gradient descent algorithm to obtain a
support vector machine model. According to the method, different dimension data are mapped through the kernel function, the data
gain weight can be determined, the linear separable effect of the mapped dimension data can be improved, and then the classification and analysis capability of the SVM can be improved.