一种DOTA2英雄的分布式表征
a distributed representation method of DOTA2 hero.
多次训练的结果表明这是一种可靠的表征方式
The results of multiple trainings shows that this is a reliable method of representation.
训练得到的英雄向量可以用来做英雄的聚类和比赛的胜负预测
The hero vector trained by this method can be used to cluster analysis or outcome prediction.
训练方法借鉴了word2vec所使用的训练方法,并且在其基础上进行了改进。
具体改进在于建立了两个huffman树分别对应英雄之间的克制关系和协作关系,这两个huffman的非叶子节点的参数向量独立,但英雄向量共享。
协同训练这两个huffman树使得英雄向量在这两个huffman树上的表现最优。
训练语料库是按照统计概率自动生成的
对于一个训练样例{a1,a2,x,b2,b1},根据a1,a2,b2,b1预测x。
若在协作huffman树中,则有a1,a2对x有增益作用,并且a2增益大于a1增益;b2,b1对x有削减作用,并且b2的削减大于b1的削减。
克制huffman树中同理。
该方法已形成初步论文。
disrepresent_of_heroes's Introduction
disrepresent_of_heroes's People
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