使用支持向量机，感知机，随机森林，决策树，k近邻，logistic，bagging，boosting，集成等多种常见算法实现多分类任务（分类）。Support vector machine, perceptron, random forest, decision tree, k-nearest neighbor, logistic, bagging, boosting, ensemble and other common algorithms are used to achieve multi classification tasks.
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使用支持向量机，感知机，随机森林，决策树，k近邻，logistic，LSTM，bagging，boosting，集成等多种常见算法实现多分类任务（三分类）。Support vector machine, perceptron, random forest, decision tree, k-nearest neighbor, logistic, bagging, boosting, LSTM, ensemble and other common algorithms are used to achieve multi classification tasks.
ypylj/Multi-Class-Classification
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使用支持向量机，感知机，随机森林，决策树，k近邻，logistic，LSTM，bagging，boosting，集成等多种常见算法实现多分类任务（三分类）。Support vector machine, perceptron, random forest, decision tree, k-nearest neighbor, logistic, bagging, boosting, LSTM, ensemble and other common algorithms are used to achieve multi classification tasks.
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