Apriori 算法的数据集
我将开发一个用于市场购物篮分析的应用程序(使用 apriori 算法),我发现了一个包含超过 90,000 条交易记录的数据集。
问题是这个数据集没有项目的名称,只包含项目的条形码。
我刚刚开始这个项目并研究 apriori 算法,任何人都可以帮助我解决这个案例,如何使用以下数据集实现该算法的最佳方法?
I am going to develop an app for Market Basket Analysis (using apriori algorithm) and I found a dataset which has more than 90,000 Transaction records .
the problem is this dataset doesn't have the name of items in it and only contains the barcode of the items .
I just start the project and doing research on apriori algorithm , can anyone help me about this case , how is the best way to implement this algorithm using the following dataset ?
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此类数据集被视为关键信息,连锁店不会为您提供这些信息,但您可以使用 SQL Server 自己生成一些示例数据集。
these kind of datasets are consider critical information and chain stores will not give you these information but you can generate some sample dataset yourself using SQL Server .
该算法的定义与对象所使用的标识符无关。另外,您没有发布“以下数据集”:P 如果您的问题是算法期望您的物品编号为 0,1,2,...,那么只需扫描您的数据集并将每个单独的条形码映射到数字。
如果您感兴趣,有一些关于如何非常有效地表示频繁项集的论文:http://www.google.de/url?sa=t&source=web&cd=1&ved=0CB8QFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu% 2Fviewdoc%2Fdownload%3Fd oi%3D10.1.1.163.4827%26rep%3Drep1%26type%3Dpdf&ei=QdVuTsn7Cc6WmQWD7sWVCg& amp;usg=AFQjCNGDG8etNN2B4GQ52pSNIfQaTH7ajQ&sig2=7r3buh8AcfJmn2CwjjobAg
The algorithm is defined independent of the identifiers used for the object. Also, you didn't post the 'following data set' :P If your problem is that the algorithm expects your items to be numbered 0,1,2,... then just scan your data set and map each individual barcode to a number.
If you're interested, there's been some papers on how to represent frequent item sets very efficiently: http://www.google.de/url?sa=t&source=web&cd=1&ved=0CB8QFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.163.4827%26rep%3Drep1%26type%3Dpdf&ei=QdVuTsn7Cc6WmQWD7sWVCg&usg=AFQjCNGDG8etNN2B4GQ52pSNIfQaTH7ajQ&sig2=7r3buh8AcfJmn2CwjjobAg
该算法不需要项目的名称。
The algorithm does not need the name of the items.