"Importing textdata from csv files"
Gary_Hearne
New Altair Community Member
I teach a data mining course to business management students (with little or no programming experience) using a combination of R and RapidMiner. I try to duplicate the examples from each package in the other so that students to appreciate the differences in usability, available algorithms and results. For obvious reasons I use the graphical process approach in RapidMiner, rather than teaching XML (which I don't know anyway).
I have two csv data sets which I use in R, neither of which I have been able to import in the appropriate format to use in RapidMiner, despite playing around with what look like sensible operator options.
sms_spam.csv has two columns, the first identifies the content of the second as "spam" or "ham", while the second is a text message. (http://www.dt.fee.unicamp.br/~tiago/smsspamcollection/). I want to import this so that I can use Naive Bayes to build a classifier for messages.
groceries.csv is an example set that comes with the arules library in R. It has multiple (unlabelled) columns, with each row representing a transaction, and as many columns used as there are items - so unstructured. I want to use association rules and/or fp-growth on this.
Any suggestions on how I can get either or both of these data sets into RapidMiner in a usable form would be greatly appreciated.
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Answers
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hi @User33136 - good to hear from you. I took a minute on your sms-spam.csv set. Is this what you're looking for?
<?xml version="1.0" encoding="UTF-8"?><process version="9.1.000"> <context> <input/> <output/> <macros/> </context> <operator activated="true" class="process" compatibility="9.1.000" expanded="true" name="Process"> <parameter key="logverbosity" value="init"/> <parameter key="random_seed" value="2001"/> <parameter key="send_mail" value="never"/> <parameter key="notification_email" value=""/> <parameter key="process_duration_for_mail" value="30"/> <parameter key="encoding" value="SYSTEM"/> <process expanded="true"> <operator activated="true" breakpoints="after" class="read_csv" compatibility="9.1.000" expanded="true" height="68" name="Read CSV" width="90" x="45" y="340"> <parameter key="csv_file" value="/Users/genzerconsulting/Desktop/sms_spam.csv"/> <parameter key="column_separators" value=","/> <parameter key="trim_lines" value="false"/> <parameter key="use_quotes" value="true"/> <parameter key="quotes_character" value="""/> <parameter key="escape_character" value="\"/> <parameter key="skip_comments" value="true"/> <parameter key="comment_characters" value="#"/> <parameter key="starting_row" value="1"/> <parameter key="parse_numbers" value="true"/> <parameter key="decimal_character" value="."/> <parameter key="grouped_digits" value="false"/> <parameter key="grouping_character" value=","/> <parameter key="infinity_representation" value=""/> <parameter key="date_format" value=""/> <parameter key="first_row_as_names" value="true"/> <list key="annotations"/> <parameter key="time_zone" value="SYSTEM"/> <parameter key="locale" value="English (United States)"/> <parameter key="encoding" value="UTF-8"/> <parameter key="read_all_values_as_polynominal" value="false"/> <list key="data_set_meta_data_information"> <parameter key="0" value="type.true.binominal.label"/> <parameter key="1" value="text.true.text.attribute"/> </list> <parameter key="read_not_matching_values_as_missings" value="false"/> <parameter key="datamanagement" value="double_array"/> <parameter key="data_management" value="auto"/> </operator> <operator activated="true" class="text:process_document_from_data" compatibility="8.1.000" expanded="true" height="82" name="Process Documents from Data" width="90" x="179" y="340"> <parameter key="create_word_vector" value="true"/> <parameter key="vector_creation" value="TF-IDF"/> <parameter key="add_meta_information" value="true"/> <parameter key="keep_text" value="false"/> <parameter key="prune_method" value="percentual"/> <parameter key="prune_below_percent" value="1.0"/> <parameter key="prune_above_percent" value="30.0"/> <parameter key="prune_below_rank" value="0.05"/> <parameter key="prune_above_rank" value="0.95"/> <parameter key="datamanagement" value="double_sparse_array"/> <parameter key="data_management" value="auto"/> <parameter key="select_attributes_and_weights" value="false"/> <list key="specify_weights"/> <process expanded="true"> <operator activated="true" class="text:transform_cases" compatibility="8.1.000" expanded="true" height="68" name="Transform Cases" width="90" x="45" y="34"> <parameter key="transform_to" value="lower case"/> </operator> <operator activated="true" class="text:tokenize" compatibility="8.1.000" expanded="true" height="68" name="Tokenize" width="90" x="179" y="34"> <parameter key="mode" value="non letters"/> <parameter key="characters" value=".:"/> <parameter key="language" value="English"/> <parameter key="max_token_length" value="3"/> </operator> <operator activated="true" class="text:filter_stopwords_english" compatibility="8.1.000" expanded="true" height="68" name="Filter Stopwords (English)" width="90" x="313" y="34"/> <operator activated="true" class="text:filter_by_length" compatibility="8.1.000" expanded="true" height="68" name="Filter Tokens (by Length)" width="90" x="447" y="34"> <parameter key="min_chars" value="4"/> <parameter key="max_chars" value="25"/> </operator> <connect from_port="document" to_op="Transform Cases" to_port="document"/> <connect from_op="Transform Cases" from_port="document" to_op="Tokenize" to_port="document"/> <connect from_op="Tokenize" from_port="document" to_op="Filter Stopwords (English)" to_port="document"/> <connect from_op="Filter Stopwords (English)" from_port="document" to_op="Filter Tokens (by Length)" to_port="document"/> <connect from_op="Filter Tokens (by Length)" from_port="document" to_port="document 1"/> <portSpacing port="source_document" spacing="0"/> <portSpacing port="sink_document 1" spacing="0"/> <portSpacing port="sink_document 2" spacing="0"/> </process> </operator> <operator activated="true" class="split_data" compatibility="9.1.000" expanded="true" height="103" name="Split Data" width="90" x="313" y="340"> <enumeration key="partitions"> <parameter key="ratio" value="0.8"/> <parameter key="ratio" value="0.2"/> </enumeration> <parameter key="sampling_type" value="automatic"/> <parameter key="use_local_random_seed" value="false"/> <parameter key="local_random_seed" value="1992"/> </operator> <operator activated="true" class="concurrency:cross_validation" compatibility="9.1.000" expanded="true" height="145" name="Cross Validation" width="90" x="514" y="136"> <parameter key="split_on_batch_attribute" value="false"/> <parameter key="leave_one_out" value="false"/> <parameter key="number_of_folds" value="10"/> <parameter key="sampling_type" value="automatic"/> <parameter key="use_local_random_seed" value="false"/> <parameter key="local_random_seed" value="1992"/> <parameter key="enable_parallel_execution" value="true"/> <process expanded="true"> <operator activated="true" class="naive_bayes" compatibility="9.1.000" expanded="true" height="82" name="Naive Bayes" width="90" x="112" y="34"> <parameter key="laplace_correction" value="true"/> </operator> <connect from_port="training set" to_op="Naive Bayes" to_port="training set"/> <connect from_op="Naive Bayes" from_port="model" to_port="model"/> <portSpacing port="source_training set" spacing="0"/> <portSpacing port="sink_model" spacing="0"/> <portSpacing port="sink_through 1" spacing="0"/> </process> <process expanded="true"> <operator activated="true" class="apply_model" compatibility="9.1.000" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34"> <list key="application_parameters"/> <parameter key="create_view" value="false"/> </operator> <operator activated="true" class="performance_binominal_classification" compatibility="9.1.000" expanded="true" height="82" name="Performance" width="90" x="179" y="34"> <parameter key="main_criterion" value="first"/> <parameter key="accuracy" value="true"/> <parameter key="classification_error" value="false"/> <parameter key="kappa" value="false"/> <parameter key="AUC (optimistic)" value="false"/> <parameter key="AUC" value="false"/> <parameter key="AUC (pessimistic)" value="false"/> <parameter key="precision" value="false"/> <parameter key="recall" value="false"/> <parameter key="lift" value="false"/> <parameter key="fallout" value="false"/> <parameter key="f_measure" value="false"/> <parameter key="false_positive" value="false"/> <parameter key="false_negative" value="false"/> <parameter key="true_positive" value="false"/> <parameter key="true_negative" value="false"/> <parameter key="sensitivity" value="false"/> <parameter key="specificity" value="false"/> <parameter key="youden" value="false"/> <parameter key="positive_predictive_value" value="false"/> <parameter key="negative_predictive_value" value="false"/> <parameter key="psep" value="false"/> <parameter key="skip_undefined_labels" value="true"/> <parameter key="use_example_weights" value="true"/> </operator> <connect from_port="model" to_op="Apply Model" to_port="model"/> <connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/> <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/> <connect from_op="Performance" from_port="performance" to_port="performance 1"/> <portSpacing port="source_model" spacing="0"/> <portSpacing port="source_test set" spacing="0"/> <portSpacing port="source_through 1" spacing="0"/> <portSpacing port="sink_test set results" spacing="0"/> <portSpacing port="sink_performance 1" spacing="0"/> <portSpacing port="sink_performance 2" spacing="0"/> </process> </operator> <operator activated="true" class="apply_model" compatibility="9.1.000" expanded="true" height="82" name="Apply Model (2)" width="90" x="648" y="340"> <list key="application_parameters"/> <parameter key="create_view" value="false"/> </operator> <operator activated="true" class="performance_binominal_classification" compatibility="9.1.000" expanded="true" height="82" name="Performance (2)" width="90" x="782" y="340"> <parameter key="main_criterion" value="first"/> <parameter key="accuracy" value="true"/> <parameter key="classification_error" value="false"/> <parameter key="kappa" value="false"/> <parameter key="AUC (optimistic)" value="false"/> <parameter key="AUC" value="false"/> <parameter key="AUC (pessimistic)" value="false"/> <parameter key="precision" value="false"/> <parameter key="recall" value="false"/> <parameter key="lift" value="false"/> <parameter key="fallout" value="false"/> <parameter key="f_measure" value="false"/> <parameter key="false_positive" value="false"/> <parameter key="false_negative" value="false"/> <parameter key="true_positive" value="false"/> <parameter key="true_negative" value="false"/> <parameter key="sensitivity" value="false"/> <parameter key="specificity" value="false"/> <parameter key="youden" value="false"/> <parameter key="positive_predictive_value" value="false"/> <parameter key="negative_predictive_value" value="false"/> <parameter key="psep" value="false"/> <parameter key="skip_undefined_labels" value="true"/> <parameter key="use_example_weights" value="true"/> </operator> <connect from_op="Read CSV" from_port="output" to_op="Process Documents from Data" to_port="example set"/> <connect from_op="Process Documents from Data" from_port="example set" to_op="Split Data" to_port="example set"/> <connect from_op="Split Data" from_port="partition 1" to_op="Cross Validation" to_port="example set"/> <connect from_op="Split Data" from_port="partition 2" to_op="Apply Model (2)" to_port="unlabelled data"/> <connect from_op="Cross Validation" from_port="model" to_op="Apply Model (2)" to_port="model"/> <connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance (2)" to_port="labelled data"/> <connect from_op="Performance (2)" from_port="performance" to_port="result 1"/> <connect from_op="Performance (2)" from_port="example set" to_port="result 2"/> <portSpacing port="source_input 1" spacing="0"/> <portSpacing port="sink_result 1" spacing="336"/> <portSpacing port="sink_result 2" spacing="0"/> <portSpacing port="sink_result 3" spacing="0"/> </process> </operator> </process>
I will give the other a try later.
Do you want me to put these on the community samples repo for your students? It may be easier for you and your students.
Scott
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Hi Scott, and thanks for your reply.To be honest, I wouldn't know where to start with the code. I only ever use the GUI, and my students freak at the very thought of having to adapt the R code I give them.I was hoping there were suitable operators available to do this - there are a few that sound like they should, but I can't get any of them to work.Gary(I would change my user name to my actual name, but apparently I lack the privileges to do this)0
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Hi Gary -
Haha no only the community manager can change the user id. I can change this to whatever you want. Let me know what your preferred 'handle' is.
That code is XML - the backbone of RapidMiner and the way people swap processes. You can learn how to do it here: https://community.rapidminer.com/discussion/37047. It's just a matter of 'copy-and-paste'. I'm attaching the same process as an .rmp file to this message if that's easier for you.
The process looks like this when you load it into RapidMiner:
and I made a folder for you on the Community Samples repo so any student can just load and run
Scott
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ok the grocery association rules one is also there:
Scott0