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<html><head><title>R: Class “transactions” — Binary Incidence Matrix for
Transactions</title>
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<table width="100%" summary="page for transactions-class {arules}"><tr><td>transactions-class {arules}</td><td align="right">R Documentation</td></tr></table>
<h2>Class “transactions” — Binary Incidence Matrix for
Transactions</h2>
<h3>Description</h3>
<p>
The <code>transactions</code> class represents transaction data used for
mining itemsets or rules. It is a direct extension of class
<code><a href="itemMatrix-class.html">itemMatrix</a></code> to store a binary incidence
matrix, item labels, and optionally transaction IDs and user IDs.
</p>
<h3>Objects from the Class</h3>
<p>
Objects are created by coercion from objects of other classes or by
calls of the form <code>new("transactions", ...)</code>.
</p>
<h3>Slots</h3>
<dl>
<dt><code>transactionInfo</code>:</dt><dd>a data.frame
with vectors of the same length as the number of
transactions. Each vector can hold additional information, e.g.,
store transaction IDs or user IDs for each transaction.</dd>
<dt><code>data</code>:</dt><dd>object of class
<code><a href="../../Matrix/html/ngCMatrix-class.html">ngCMatrix</a></code> to store the
binary incidence matrix (see
<code><a href="itemMatrix-class.html">itemMatrix</a></code> class)</dd>
<dt><code>itemInfo</code>:</dt><dd>a data.frame to store
item labels (see <code><a href="itemMatrix-class.html">itemMatrix</a></code> class)</dd>
</dl>
<h3>Extends</h3>
<p>
Class <code><a href="itemMatrix-class.html">itemMatrix</a></code>, directly.
</p>
<h3>Methods</h3>
<dl>
<dt>coerce</dt><dd><code>signature(from = "matrix", to = "transactions")</code>;
produces a transactions data set from a binary incidence matrix.
The row names are used as item labels and the column names are
stores as transaction IDs.
</dd>
<dt>coerce</dt><dd><code>signature(from = "list", to = "transactions")</code>;
produces a transactions data set from a list. The names of the
items in the list are used as item labels and the item IDs and the
incidence matrix is produced automatically.
</dd>
<dt>coerce</dt><dd><code>signature(from = "transactions", to = "matrix")</code></dd>
<dt>coerce</dt><dd><code>signature(from = "transactions", to = "list")</code></dd>
<dt>coerce</dt><dd><code>signature(from = "data.frame", to = "transactions")</code>;
recodes the data frame containing only categorical variables (all
have to be factors) into a binary transaction data set. The needed
number of dummy items are automatically generated. The item
labels are generated by concatenating variable names and levels with
a <span class="samp">"="</span>.
The variable names and levels are stored in the labels data frame
as the components <code>variables</code> and <code>levels</code>.
Note that <code>NA</code> in one of the levels is replaced by the string
“NA”, i.e. the special meaning is lost.</dd>
<dt>coerce</dt><dd><code>signature(from = "transactions", to = "data.frame")</code>;
represents the set of transactions in a printable form
as a data.frame.
Note that this does not reverse coercion from data.frame
to <code>transactions</code>.</dd>
<dt>labels</dt><dd><code>signature(x = "transactions")</code>;
returns the labels (item labels and transaction IDs)
for the incidence matrix as a list of two vectors named <code>items</code>
and <code>transactionID</code>.</dd>
<dt>transactionInfo<-</dt><dd><code>signature(x = "transactions")</code>;
replaces the transactionInfo data frame</dd>
<dt>transactionInfo</dt><dd><code>signature(x = "transactions")</code>;
returns transactionInfo</dd>
<dt>show</dt><dd><code>signature(object = "transactions")</code></dd>
<dt>summary</dt><dd><code>signature(object = "transactions")</code></dd>
</dl>
<h3>See Also</h3>
<p>
<code><a href="Xtrct-methods.html">[-methods</a></code>,
<code><a href="LIST.html">LIST</a></code>,
<code><a href="WRITE.html">WRITE</a></code>,
<code><a href="combine.html">c</a></code>,
<code><a href="image.html">image</a></code>,
<code><a href="inspect.html">inspect</a></code>,
<code><a href="read.transactions.html">read.transactions</a></code>,
<code><a href="random.transactions.html">random.transactions</a></code>,
<code><a href="sets.html">sets</a></code>,
<code><a href="itemMatrix-class.html">itemMatrix-class</a></code>
</p>
<h3>Examples</h3>
<pre>
## 1. example: creating transactions form a list
a_list <- list(
c("a","b","c"),
c("a","b"),
c("a","b","d"),
c("c","e"),
c("a","b","d","e")
)
## set transaction names
names(a_list) <- paste("Tr",c(1:5), sep = "")
a_list
## coerce into transactions
trans <- as(a_list, "transactions")
## analyze transactions
summary(trans)
image(trans)
## 2. example: creating transactions from a matrix
a_matrix <- matrix(
c(1,1,1,0,0,
1,1,0,0,0,
1,1,0,1,0,
0,0,1,0,1,
1,1,0,1,1), ncol = 5)
## set dim names
dimnames(a_matrix) <- list(
c("a","b","c","d","e"),
paste("Tr",c(1:5), sep = ""))
a_matrix
## coerce
trans2 <- as(a_matrix, "transactions")
trans2
## example 3: creating transactions from data.frame
a_data.frame <- data.frame(
age = as.factor(c(6,8,7,6,9,5)),
grade = as.factor(c(1,3,1,1,4,1)))
## note: all attributes have to be factors
a_data.frame
## coerce
trans3 <- as(a_data.frame, "transactions")
image(trans3)
## 3. example creating from data.frame with NA
a_df <- sample(c(LETTERS[1:5], NA),10,TRUE)
a_df <- data.frame(X = a_df, Y = sample(a_df))
a_df
trans3 <- as(a_df, "transactions")
trans3
as(trans3, "data.frame")
</pre>
<hr><div align="center">[Package <em>arules</em> version 0.6-6 <a href="00Index.html">Index]</a></div>
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