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K-NN with training and testing CSV sets
Hi there,
[Edit: Solved... The training and testing files did not have the same attribute names. Now it works just fine!]
I'm testing out Rapid Miner 5.0, and I have a problem with a classic setup. I have two CSV input files (train and test), and I want to train the K-NN on the train file, and test it on the test file (the usual setup basically ::) ).
The problem is that the K-NN predicts the same value for each test example. When I use the Weka implementation (W-IBk), I don't have that problem.
Here is my process:
- R
[Edit: Solved... The training and testing files did not have the same attribute names. Now it works just fine!]
I'm testing out Rapid Miner 5.0, and I have a problem with a classic setup. I have two CSV input files (train and test), and I want to train the K-NN on the train file, and test it on the test file (the usual setup basically ::) ).
The problem is that the K-NN predicts the same value for each test example. When I use the Weka implementation (W-IBk), I don't have that problem.
Here is my process:
Thank you for any help!
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.0">
<context>
<input>
<location/>
</input>
<output>
<location/>
<location/>
</output>
<macros/>
</context>
<operator activated="true" class="process" expanded="true" name="Process">
<process expanded="true" height="316" width="577">
<operator activated="true" class="read_csv" expanded="true" height="60" name="Read CSV TRAIN" width="90" x="45" y="30">
<parameter key="file_name" value="train.csv"/>
<parameter key="use_first_row_as_attribute_names" value="false"/>
</operator>
<operator activated="true" class="numerical_to_real" expanded="true" height="76" name="Numerical to Real" width="90" x="179" y="30"/>
<operator activated="true" class="set_role" expanded="true" height="76" name="Set Role" width="90" x="313" y="30">
<parameter key="name" value="train.csv_5"/>
<parameter key="target_role" value="label"/>
</operator>
<operator activated="true" class="k_nn" expanded="true" height="76" name="k-NN" width="90" x="447" y="30">
<parameter key="k" value="4"/>
</operator>
<operator activated="true" class="read_csv" expanded="true" height="60" name="Read CSV TEST" width="90" x="45" y="165">
<parameter key="file_name" value="test.csv"/>
<parameter key="use_first_row_as_attribute_names" value="false"/>
</operator>
<operator activated="true" class="numerical_to_real" expanded="true" height="76" name="Numerical to Real (2)" width="90" x="179" y="165"/>
<operator activated="true" class="set_role" expanded="true" height="76" name="Set Role (2)" width="90" x="313" y="165">
<parameter key="name" value="test.csv_5"/>
<parameter key="target_role" value="label"/>
</operator>
<operator activated="true" class="apply_model" expanded="true" height="76" name="Apply Model" width="90" x="447" y="165">
<list key="application_parameters"/>
</operator>
<connect from_op="Read CSV TRAIN" from_port="output" to_op="Numerical to Real" to_port="example set input"/>
<connect from_op="Numerical to Real" from_port="example set output" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="k-NN" to_port="training set"/>
<connect from_op="k-NN" from_port="model" to_op="Apply Model" to_port="model"/>
<connect from_op="Read CSV TEST" from_port="output" to_op="Numerical to Real (2)" to_port="example set input"/>
<connect from_op="Numerical to Real (2)" from_port="example set output" to_op="Set Role (2)" to_port="example set input"/>
<connect from_op="Set Role (2)" from_port="example set output" to_op="Apply Model" to_port="unlabelled data"/>
<connect from_op="Apply Model" from_port="labelled data" 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>
- R
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