Applying Word2vec on a dataset of texts

AC24

Hi, I created ad SVM model for text classification and I want to share the process with you to have any advise to improve it. The purpose of this classificator is to classify a dataset of comments, reviews, or sentences in general, into positive and negative and the dataset I used for its training was made of 2400 tweets (1200 positive and 1200 negative). 

I also would ask you if there is a way to implement in this process a word2vec embedding, or how can I create an alternative process for this purpose. If I try to apply word2vec on the opetators loop and loop collection, this return some errors and I don't know how to give as input a dataset of sentences (my dataset has the attributs "text" and "sentiment") and not a whole text or a collaction of long texts. 

Here is the code of the process:

<?xml version="1.0" encoding="UTF-8"?><process version="9.10.011">

  <context>

    <input/>

    <output/>

    <macros/>

  </context>

  <operator activated="true" class="process" compatibility="9.10.011" 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" class="retrieve" compatibility="9.10.011" expanded="true" height="68" name="Retrieve clean_dataset2" width="90" x="45" y="136">

        <parameter key="repository_entry" value="clean_dataset2"/>

      </operator>

      <operator activated="true" class="operator_toolbox:extract_sentiment" compatibility="2.14.000" expanded="true" height="103" name="Extract Sentiment" width="90" x="179" y="136">

        <parameter key="model" value="vader"/>

        <parameter key="text_attribute" value="text"/>

        <parameter key="show_advanced_output" value="true"/>

        <parameter key="use_default_tokenization_regex" value="true"/>

        <parameter key="tokenization_regex" value=".*"/>

        <list key="additional_words"/>

      </operator>

      <operator activated="true" class="nominal_to_text" compatibility="9.10.011" expanded="true" height="82" name="Nominal to Text" width="90" x="313" y="136">

        <parameter key="attribute_filter_type" value="single"/>

        <parameter key="attribute" value="text"/>

        <parameter key="attributes" value="text|sentiment"/>

        <parameter key="use_except_expression" value="false"/>

        <parameter key="value_type" value="nominal"/>

        <parameter key="use_value_type_exception" value="false"/>

        <parameter key="except_value_type" value="file_path"/>

        <parameter key="block_type" value="single_value"/>

        <parameter key="use_block_type_exception" value="false"/>

        <parameter key="except_block_type" value="single_value"/>

        <parameter key="invert_selection" value="false"/>

        <parameter key="include_special_attributes" value="false"/>

      </operator>

      <operator activated="true" class="text:process_document_from_data" compatibility="9.4.000" expanded="true" height="82" name="Process Documents from Data" width="90" x="447" y="136">

        <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="true"/>

        <parameter key="prune_method" value="percentual"/>

        <parameter key="prune_below_percent" value="1.0"/>

        <parameter key="prune_above_percent" value="99.0"/>

        <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:tokenize" compatibility="9.4.000" 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:transform_cases" compatibility="9.4.000" expanded="true" height="68" name="Transform Cases" width="90" x="313" y="34">

            <parameter key="transform_to" value="lower case"/>

          </operator>

          <operator activated="true" class="text:filter_stopwords_english" compatibility="9.4.000" expanded="true" height="68" name="Filter Stopwords (English)" width="90" x="447" y="34"/>

          <operator activated="true" class="text:filter_by_length" compatibility="9.4.000" expanded="true" height="68" name="Filter Tokens (by Length)" width="90" x="581" y="34">

            <parameter key="min_chars" value="4"/>

            <parameter key="max_chars" value="999"/>

          </operator>

          <connect from_port="document" to_op="Tokenize" to_port="document"/>

          <connect from_op="Tokenize" from_port="document" to_op="Transform Cases" to_port="document"/>

          <connect from_op="Transform Cases" 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="select_attributes" compatibility="9.10.011" expanded="true" height="82" name="Select Attributes" width="90" x="581" y="136">

        <parameter key="attribute_filter_type" value="no_missing_values"/>

        <parameter key="attribute" value=""/>

        <parameter key="attributes" value="|sentiment|text"/>

        <parameter key="use_except_expression" value="false"/>

        <parameter key="value_type" value="attribute_value"/>

        <parameter key="use_value_type_exception" value="false"/>

        <parameter key="except_value_type" value="time"/>

        <parameter key="block_type" value="attribute_block"/>

        <parameter key="use_block_type_exception" value="false"/>

        <parameter key="except_block_type" value="value_matrix_row_start"/>

        <parameter key="invert_selection" value="false"/>

        <parameter key="include_special_attributes" value="true"/>

      </operator>

      <operator activated="true" class="store" compatibility="9.10.011" expanded="true" height="68" name="Store wordlist" width="90" x="380" y="289">

        <parameter key="repository_entry" value="Wordlist"/>

      </operator>

      <operator activated="true" class="set_role" compatibility="9.10.011" expanded="true" height="82" name="Set Role" width="90" x="715" y="136">

        <parameter key="attribute_name" value="sentiment"/>

        <parameter key="target_role" value="label"/>

        <list key="set_additional_roles">

          <parameter key="Score" value="regular"/>

        </list>

      </operator>

      <operator activated="true" class="split_data" compatibility="9.10.011" expanded="true" height="103" name="Split Data" width="90" x="581" y="238">

        <enumeration key="partitions">

          <parameter key="ratio" value="0.7"/>

          <parameter key="ratio" value="0.3"/>

        </enumeration>

        <parameter key="sampling_type" value="stratified sampling"/>

        <parameter key="use_local_random_seed" value="false"/>

        <parameter key="local_random_seed" value="1992"/>

      </operator>

      <operator activated="true" class="concurrency:cross_validation" compatibility="9.10.011" expanded="true" height="145" name="Cross Validation" width="90" x="715" y="238">

        <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="support_vector_machine_libsvm" compatibility="9.10.011" expanded="true" height="82" name="SVM (2)" width="90" x="179" y="136">

            <parameter key="svm_type" value="C-SVC"/>

            <parameter key="kernel_type" value="linear"/>

            <parameter key="degree" value="3"/>

            <parameter key="gamma" value="0.05"/>

            <parameter key="coef0" value="0.0"/>

            <parameter key="C" value="0.0"/>

            <parameter key="nu" value="0.5"/>

            <parameter key="cache_size" value="80"/>

            <parameter key="epsilon" value="1.0"/>

            <parameter key="p" value="0.1"/>

            <list key="class_weights"/>

            <parameter key="shrinking" value="true"/>

            <parameter key="calculate_confidences" value="true"/>

            <parameter key="confidence_for_multiclass" value="false"/>

          </operator>

          <connect from_port="training set" to_op="SVM (2)" to_port="training set"/>

          <connect from_op="SVM (2)" 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="9.10.011" expanded="true" height="82" name="Apply Model" width="90" x="112" y="85">

            <list key="application_parameters"/>

            <parameter key="create_view" value="false"/>

          </operator>

          <operator activated="true" class="performance" compatibility="9.10.011" expanded="true" height="82" name="Performance" width="90" x="179" y="187">

            <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="store" compatibility="9.10.011" expanded="true" height="68" name="Store model" width="90" x="849" y="238">

        <parameter key="repository_entry" value="My SVM model"/>

      </operator>

      <operator activated="true" class="apply_model" compatibility="9.10.011" expanded="true" height="82" name="Apply Model (2)" width="90" x="447" y="442">

        <list key="application_parameters"/>

        <parameter key="create_view" value="false"/>

      </operator>

      <operator activated="true" class="performance" compatibility="9.10.011" expanded="true" height="82" name="Performance (2)" width="90" x="648" y="442">

        <parameter key="use_example_weights" value="true"/>

      </operator>

      <connect from_op="Retrieve clean_dataset2" from_port="output" to_op="Extract Sentiment" to_port="exa"/>

      <connect from_op="Extract Sentiment" from_port="exa" to_op="Nominal to Text" to_port="example set input"/>

      <connect from_op="Nominal to Text" from_port="example set output" to_op="Process Documents from Data" to_port="example set"/>

      <connect from_op="Process Documents from Data" from_port="example set" to_op="Select Attributes" to_port="example set input"/>

      <connect from_op="Process Documents from Data" from_port="word list" to_op="Store wordlist" to_port="input"/>

      <connect from_op="Select Attributes" 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="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="Store model" to_port="input"/>

      <connect from_op="Store model" from_port="through" 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="Apply Model (2)" from_port="model" to_port="result 2"/>

      <connect from_op="Performance (2)" from_port="performance" to_port="result 1"/>

      <connect from_op="Performance (2)" from_port="example set" to_port="result 3"/>

      <portSpacing port="source_input 1" spacing="0"/>

      <portSpacing port="sink_result 1" spacing="0"/>

      <portSpacing port="sink_result 2" spacing="0"/>

      <portSpacing port="sink_result 3" spacing="0"/>

      <portSpacing port="sink_result 4" spacing="0"/>

    </process>

  </operator>

</process>

I also share an image of the process.