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Original source:Tuo End number according to the tribe public number

 

Association rule mining is an unsupervised learning method that mines rules from transaction data. It helps to find relationships in the data set and items that appear together. In this article, I’ll explain how to extract association rules in R. The association rule model applies to transaction data. An example of transaction data could be a customer’s shopping history.

The first thing in data analysis is to understand the target data structure and content. For learning purposes, I think it’s better to use a simple data set. Once we know this model, we can easily apply it to more complex data sets. In this case, we use transaction data from grocery stores. First, we create a data box and convert it to the transaction type.

Read the data

N =500 # trans < -data.frame () # data frame to collect dataCopy the code

Create data and collect it into the transaction data box.

For (I in 1:n) {count < -sample (1:3, 1) # count from 1 to 3 if(I %% 2 == 1) {if(! add_product %in% selected) { tran <- data.frame(items = add_product, tid = i)Copy the code

Check the data in the transaction data box.

Next, we need to convert the generated data box to the transaction data type.


 as(split([, "items"], [, "tid"]), "transa")
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To examine the contents of the transaction data, we use the inspect() command.

Mining rules

sort(rules_1, dby = "confidence")
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.

We take the first RHS item (rule after item) from the list above to check the rule for that item. But if you know the target item, you can just write RHS =”melon” in the argument.

 inspect(rules_1@rhs[1])
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> rhs_item <- gsub("\\}","", rhs)
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We establish rules for our RHS_item

Sort by “confidence” and check the rules


sort(rules_2, "confidence")
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Result visualization

Finally, we plot the first five rules from rule set _2.

> plot(rules_2[1:5])
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Draw all rules

Interactive visualization

Draw the first five rules

precision	 =  3
igraphLayout	 =  layout_nicely
list(nodes = nodes, edges = edges, nodesToDataframe = nodesToDataframe, 
            edgesToDataframe = edgesToDataframe,
x$legend <- legend
    htmlwidgets::createWidget( x, width = width, 
        height = height)
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Draw all rules

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