文件名称:plot_multilabel
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Multilabel是一个分类算法，数据集生成具有一定规则性；规则如下：
pick the number of labels: n ~ Poisson(n_labels)
n times, choose a class c: c ~ Multinomial(theta)
pick the document length: k ~ Poisson(length)
k times, choose a word: w ~ Multinomial(theta_c)-This example simulates a multi-label document classification problem. The dataset is generated randomly based on the following process:
pick the number of labels: n ~ Poisson(n_labels)
n times, choose a class c: c ~ Multinomial(theta)
pick the document length: k ~ Poisson(length)
k times, choose a word: w ~ Multinomial(theta_c)
In the above process, rejection sampling is used to make sure that n is more than 2, and that the document length is never zero. Likewise, we reject classes which have already been chosen. The documents that are assigned to both classes are plotted surrounded by two colored circles.
pick the number of labels: n ~ Poisson(n_labels)
n times, choose a class c: c ~ Multinomial(theta)
pick the document length: k ~ Poisson(length)
k times, choose a word: w ~ Multinomial(theta_c)-This example simulates a multi-label document classification problem. The dataset is generated randomly based on the following process:
pick the number of labels: n ~ Poisson(n_labels)
n times, choose a class c: c ~ Multinomial(theta)
pick the document length: k ~ Poisson(length)
k times, choose a word: w ~ Multinomial(theta_c)
In the above process, rejection sampling is used to make sure that n is more than 2, and that the document length is never zero. Likewise, we reject classes which have already been chosen. The documents that are assigned to both classes are plotted surrounded by two colored circles.
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plot_multilabel.py