Export dendrogram from a cluster / label leafes of dendrogram
Janito
New Altair Community Member
Hello everyone!
I tried to apply a hierachical cluster on my data and the output was an dendrogram. My problem now is that none of the leafes of the dendrogram is labeled with an info (I dont know which leaf belongs to which data) and I couldn't find an option to export my dendrogram into an file (for example excel).
Somebody know how to solve this problem please?
Thanks in advance!
Greetings
Janito
Tagged:
0
Best Answer
-
Hi @JanitoI don't think there is any way to export the graph itself or the underlying data, sorry. The same information is encoded in the folder view and you can click on data points to show the data row itself. For this, the data needs an ID before the clustering is applied. Below is a sample process and a screenshot.Hope this helps,
Ingo<?xml version="1.0" encoding="UTF-8"?><process version="9.3.000-SNAPSHOT"><br> <context><br> <input/><br> <output/><br> <macros/><br> </context><br> <operator activated="true" class="process" compatibility="9.3.000-SNAPSHOT" expanded="true" name="Process"><br> <parameter key="logverbosity" value="init"/><br> <parameter key="random_seed" value="2001"/><br> <parameter key="send_mail" value="never"/><br> <parameter key="notification_email" value=""/><br> <parameter key="process_duration_for_mail" value="30"/><br> <parameter key="encoding" value="UTF-8"/><br> <process expanded="true"><br> <operator activated="true" class="generate_data" compatibility="9.3.000-SNAPSHOT" expanded="true" height="68" name="Generate Data" width="90" x="45" y="34"><br> <parameter key="target_function" value="gaussian mixture clusters"/><br> <parameter key="number_examples" value="1000"/><br> <parameter key="number_of_attributes" value="2"/><br> <parameter key="attributes_lower_bound" value="-10.0"/><br> <parameter key="attributes_upper_bound" value="10.0"/><br> <parameter key="gaussian_standard_deviation" value="10.0"/><br> <parameter key="largest_radius" value="10.0"/><br> <parameter key="use_local_random_seed" value="false"/><br> <parameter key="local_random_seed" value="1992"/><br> <parameter key="datamanagement" value="double_array"/><br> <parameter key="data_management" value="auto"/><br> </operator><br> <operator activated="true" class="select_attributes" compatibility="9.3.000-SNAPSHOT" expanded="true" height="82" name="Select Attributes" width="90" x="179" y="34"><br> <parameter key="attribute_filter_type" value="single"/><br> <parameter key="attribute" value="label"/><br> <parameter key="attributes" value=""/><br> <parameter key="use_except_expression" value="false"/><br> <parameter key="value_type" value="attribute_value"/><br> <parameter key="use_value_type_exception" value="false"/><br> <parameter key="except_value_type" value="time"/><br> <parameter key="block_type" value="attribute_block"/><br> <parameter key="use_block_type_exception" value="false"/><br> <parameter key="except_block_type" value="value_matrix_row_start"/><br> <parameter key="invert_selection" value="true"/><br> <parameter key="include_special_attributes" value="true"/><br> </operator><br> <operator activated="true" class="generate_id" compatibility="9.3.000-SNAPSHOT" expanded="true" height="82" name="Generate ID" width="90" x="313" y="34"><br> <parameter key="create_nominal_ids" value="false"/><br> <parameter key="offset" value="0"/><br> </operator><br> <operator activated="true" class="agglomerative_clustering" compatibility="9.3.000-SNAPSHOT" expanded="true" height="82" name="Clustering" width="90" x="447" y="34"><br> <parameter key="mode" value="SingleLink"/><br> <parameter key="measure_types" value="MixedMeasures"/><br> <parameter key="mixed_measure" value="MixedEuclideanDistance"/><br> <parameter key="nominal_measure" value="NominalDistance"/><br> <parameter key="numerical_measure" value="EuclideanDistance"/><br> <parameter key="divergence" value="GeneralizedIDivergence"/><br> <parameter key="kernel_type" value="radial"/><br> <parameter key="kernel_gamma" value="1.0"/><br> <parameter key="kernel_sigma1" value="1.0"/><br> <parameter key="kernel_sigma2" value="0.0"/><br> <parameter key="kernel_sigma3" value="2.0"/><br> <parameter key="kernel_degree" value="3.0"/><br> <parameter key="kernel_shift" value="1.0"/><br> <parameter key="kernel_a" value="1.0"/><br> <parameter key="kernel_b" value="0.0"/><br> </operator><br> <connect from_op="Generate Data" from_port="output" to_op="Select Attributes" to_port="example set input"/><br> <connect from_op="Select Attributes" from_port="example set output" to_op="Generate ID" to_port="example set input"/><br> <connect from_op="Generate ID" from_port="example set output" to_op="Clustering" to_port="example set"/><br> <connect from_op="Clustering" from_port="cluster model" to_port="result 1"/><br> <portSpacing port="source_input 1" spacing="0"/><br> <portSpacing port="sink_result 1" spacing="0"/><br> <portSpacing port="sink_result 2" spacing="0"/><br> </process><br> </operator><br></process>
1
Answers
-
Hi @JanitoI don't think there is any way to export the graph itself or the underlying data, sorry. The same information is encoded in the folder view and you can click on data points to show the data row itself. For this, the data needs an ID before the clustering is applied. Below is a sample process and a screenshot.Hope this helps,
Ingo<?xml version="1.0" encoding="UTF-8"?><process version="9.3.000-SNAPSHOT"><br> <context><br> <input/><br> <output/><br> <macros/><br> </context><br> <operator activated="true" class="process" compatibility="9.3.000-SNAPSHOT" expanded="true" name="Process"><br> <parameter key="logverbosity" value="init"/><br> <parameter key="random_seed" value="2001"/><br> <parameter key="send_mail" value="never"/><br> <parameter key="notification_email" value=""/><br> <parameter key="process_duration_for_mail" value="30"/><br> <parameter key="encoding" value="UTF-8"/><br> <process expanded="true"><br> <operator activated="true" class="generate_data" compatibility="9.3.000-SNAPSHOT" expanded="true" height="68" name="Generate Data" width="90" x="45" y="34"><br> <parameter key="target_function" value="gaussian mixture clusters"/><br> <parameter key="number_examples" value="1000"/><br> <parameter key="number_of_attributes" value="2"/><br> <parameter key="attributes_lower_bound" value="-10.0"/><br> <parameter key="attributes_upper_bound" value="10.0"/><br> <parameter key="gaussian_standard_deviation" value="10.0"/><br> <parameter key="largest_radius" value="10.0"/><br> <parameter key="use_local_random_seed" value="false"/><br> <parameter key="local_random_seed" value="1992"/><br> <parameter key="datamanagement" value="double_array"/><br> <parameter key="data_management" value="auto"/><br> </operator><br> <operator activated="true" class="select_attributes" compatibility="9.3.000-SNAPSHOT" expanded="true" height="82" name="Select Attributes" width="90" x="179" y="34"><br> <parameter key="attribute_filter_type" value="single"/><br> <parameter key="attribute" value="label"/><br> <parameter key="attributes" value=""/><br> <parameter key="use_except_expression" value="false"/><br> <parameter key="value_type" value="attribute_value"/><br> <parameter key="use_value_type_exception" value="false"/><br> <parameter key="except_value_type" value="time"/><br> <parameter key="block_type" value="attribute_block"/><br> <parameter key="use_block_type_exception" value="false"/><br> <parameter key="except_block_type" value="value_matrix_row_start"/><br> <parameter key="invert_selection" value="true"/><br> <parameter key="include_special_attributes" value="true"/><br> </operator><br> <operator activated="true" class="generate_id" compatibility="9.3.000-SNAPSHOT" expanded="true" height="82" name="Generate ID" width="90" x="313" y="34"><br> <parameter key="create_nominal_ids" value="false"/><br> <parameter key="offset" value="0"/><br> </operator><br> <operator activated="true" class="agglomerative_clustering" compatibility="9.3.000-SNAPSHOT" expanded="true" height="82" name="Clustering" width="90" x="447" y="34"><br> <parameter key="mode" value="SingleLink"/><br> <parameter key="measure_types" value="MixedMeasures"/><br> <parameter key="mixed_measure" value="MixedEuclideanDistance"/><br> <parameter key="nominal_measure" value="NominalDistance"/><br> <parameter key="numerical_measure" value="EuclideanDistance"/><br> <parameter key="divergence" value="GeneralizedIDivergence"/><br> <parameter key="kernel_type" value="radial"/><br> <parameter key="kernel_gamma" value="1.0"/><br> <parameter key="kernel_sigma1" value="1.0"/><br> <parameter key="kernel_sigma2" value="0.0"/><br> <parameter key="kernel_sigma3" value="2.0"/><br> <parameter key="kernel_degree" value="3.0"/><br> <parameter key="kernel_shift" value="1.0"/><br> <parameter key="kernel_a" value="1.0"/><br> <parameter key="kernel_b" value="0.0"/><br> </operator><br> <connect from_op="Generate Data" from_port="output" to_op="Select Attributes" to_port="example set input"/><br> <connect from_op="Select Attributes" from_port="example set output" to_op="Generate ID" to_port="example set input"/><br> <connect from_op="Generate ID" from_port="example set output" to_op="Clustering" to_port="example set"/><br> <connect from_op="Clustering" from_port="cluster model" to_port="result 1"/><br> <portSpacing port="source_input 1" spacing="0"/><br> <portSpacing port="sink_result 1" spacing="0"/><br> <portSpacing port="sink_result 2" spacing="0"/><br> </process><br> </operator><br></process>
1 -
Hallo Ingo,thanks for your answer. In this case I will try to use my data for further processes.Thanks to the help of the nice community I already prepared my data perfectly for further analysis!GrüßeJanito3