how to modify the attribute imported from csv
kukuzry
New Altair Community Member
I am new, and use readcsv read data. The data is row-major, that is, the sample is along the col and attribute is along the row, which is 3*80 matrix
I have another csv representing OUTPUT, which is 1*80
How can I do that in rapidminer to make it trained by neural network?
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.013">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.3.013" expanded="true" name="Process">
<process expanded="true">
<operator activated="true" class="read_csv" compatibility="5.3.013" expanded="true" height="60" name="Read CSV" width="90" x="45" y="75">
<parameter key="csv_file" value="E:\all.csv"/>
<parameter key="column_separators" value=","/>
<parameter key="use_quotes" value="false"/>
<parameter key="first_row_as_names" value="false"/>
<list key="annotations"/>
<list key="data_set_meta_data_information"/>
</operator>
<operator activated="true" class="transpose" compatibility="5.3.013" expanded="true" height="76" name="Transpose" width="90" x="179" y="75"/>
<connect from_op="Read CSV" from_port="output" to_op="Transpose" to_port="example set input"/>
<connect from_op="Transpose" from_port="example set output" to_port="result 1"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
</process>
</operator>
</process>
I have another csv representing OUTPUT, which is 1*80
How can I do that in rapidminer to make it trained by neural network?
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.013">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="5.3.013" expanded="true" name="Process">
<process expanded="true">
<operator activated="true" class="read_csv" compatibility="5.3.013" expanded="true" height="60" name="Read CSV" width="90" x="45" y="75">
<parameter key="csv_file" value="E:\all.csv"/>
<parameter key="column_separators" value=","/>
<parameter key="use_quotes" value="false"/>
<parameter key="first_row_as_names" value="false"/>
<list key="annotations"/>
<list key="data_set_meta_data_information"/>
</operator>
<operator activated="true" class="transpose" compatibility="5.3.013" expanded="true" height="76" name="Transpose" width="90" x="179" y="75"/>
<connect from_op="Read CSV" from_port="output" to_op="Transpose" to_port="example set input"/>
<connect from_op="Transpose" from_port="example set output" to_port="result 1"/>
<portSpacing port="source_input 1" spacing="0"/>
<portSpacing port="sink_result 1" spacing="0"/>
<portSpacing port="sink_result 2" spacing="0"/>
</process>
</operator>
</process>
0
Answers
-
HI,
you did not tell us anything about the type of your data etc. Using the Transpose operator is a first step. If you have only numerical values in your data table, you can define the target variable by setting its role to "label" with the Set Role operator, then you can use the Neural Net operator to create a neural net model.
Best regards,
Marius0