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A1 06 Model using cross validation (k-NN).rmp
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A1 06 Model using cross validation (k-NN).rmp
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<?xml version="1.0" encoding="UTF-8"?><process version="9.6.000">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.6.000" 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" class="retrieve" compatibility="9.6.000" expanded="true" height="68" name="Retrieve AirBnB Full" width="90" x="45" y="34">
<parameter key="repository_entry" value="AirBnB Full"/>
</operator>
<operator activated="true" class="subprocess" compatibility="9.6.000" expanded="true" height="82" name="Subprocess" width="90" x="246" y="34">
<process expanded="true">
<operator activated="true" class="filter_examples" compatibility="9.6.000" expanded="true" height="103" name="Filter Examples (2)" width="90" x="112" y="34">
<parameter key="parameter_expression" value=""/>
<parameter key="condition_class" value="custom_filters"/>
<parameter key="invert_filter" value="false"/>
<list key="filters_list">
<parameter key="filters_entry_key" value="reviews_per_month.is_not_missing."/>
</list>
<parameter key="filters_logic_and" value="true"/>
<parameter key="filters_check_metadata" value="true"/>
</operator>
<operator activated="true" class="discretize_by_user_specification" compatibility="9.6.000" expanded="true" height="103" name="Discretize (2)" width="90" x="112" y="136">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="single"/>
<parameter key="attribute" value="reviews_per_month"/>
<parameter key="attributes" value=""/>
<parameter key="use_except_expression" value="false"/>
<parameter key="value_type" value="numeric"/>
<parameter key="use_value_type_exception" value="false"/>
<parameter key="except_value_type" value="real"/>
<parameter key="block_type" value="value_series"/>
<parameter key="use_block_type_exception" value="false"/>
<parameter key="except_block_type" value="value_series_end"/>
<parameter key="invert_selection" value="false"/>
<parameter key="include_special_attributes" value="false"/>
<list key="classes">
<parameter key="viable " value="1.0"/>
<parameter key="unviable" value="Infinity"/>
</list>
</operator>
<operator activated="true" class="set_role" compatibility="9.6.000" expanded="true" height="82" name="Set Role (3)" width="90" x="112" y="238">
<parameter key="attribute_name" value="reviews_per_month"/>
<parameter key="target_role" value="label"/>
<list key="set_additional_roles"/>
</operator>
<operator activated="true" class="operator_toolbox:smote" compatibility="2.3.000" expanded="true" height="82" name="SMOTE Upsampling (2)" width="90" x="246" y="34">
<parameter key="number_of_neighbours" value="5"/>
<parameter key="normalize" value="true"/>
<parameter key="equalize_classes" value="true"/>
<parameter key="upsampling_size" value="1000"/>
<parameter key="auto_detect_minority_class" value="true"/>
<parameter key="round_integers" value="true"/>
<parameter key="nominal_change_rate" value="0.5"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="2020"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="9.6.000" expanded="true" height="82" name="Select Attributes (3)" width="90" x="246" y="136">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value="|calculated_host_listings_count|id|number_of_reviews|price|reviews_per_month|room_type|viability "/>
<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="true"/>
<parameter key="include_special_attributes" value="false"/>
</operator>
<operator activated="true" class="weight_by_information_gain" compatibility="9.6.000" expanded="true" height="82" name="Weight by Information Gain (2)" width="90" x="313" y="238">
<parameter key="normalize_weights" value="false"/>
<parameter key="sort_weights" value="true"/>
<parameter key="sort_direction" value="descending"/>
</operator>
<operator activated="true" class="select_by_weights" compatibility="9.6.000" expanded="true" height="103" name="Select by Weights (2)" width="90" x="447" y="85">
<parameter key="weight_relation" value="top k"/>
<parameter key="weight" value="1.0"/>
<parameter key="k" value="8"/>
<parameter key="p" value="0.5"/>
<parameter key="deselect_unknown" value="true"/>
<parameter key="use_absolute_weights" value="true"/>
</operator>
<operator activated="true" class="sample_stratified" compatibility="9.6.000" expanded="true" height="82" name="Sample (Stratified) (2)" width="90" x="581" y="34">
<parameter key="sample" value="absolute"/>
<parameter key="sample_size" value="10000"/>
<parameter key="sample_ratio" value="0.1"/>
<parameter key="use_local_random_seed" value="true"/>
<parameter key="local_random_seed" value="2020"/>
</operator>
<connect from_port="in 1" to_op="Filter Examples (2)" to_port="example set input"/>
<connect from_op="Filter Examples (2)" from_port="example set output" to_op="Discretize (2)" to_port="example set input"/>
<connect from_op="Discretize (2)" from_port="example set output" to_op="Set Role (3)" to_port="example set input"/>
<connect from_op="Set Role (3)" from_port="example set output" to_op="SMOTE Upsampling (2)" to_port="exa"/>
<connect from_op="SMOTE Upsampling (2)" from_port="ups" to_op="Select Attributes (3)" to_port="example set input"/>
<connect from_op="Select Attributes (3)" from_port="example set output" to_op="Weight by Information Gain (2)" to_port="example set"/>
<connect from_op="Weight by Information Gain (2)" from_port="weights" to_op="Select by Weights (2)" to_port="weights"/>
<connect from_op="Weight by Information Gain (2)" from_port="example set" to_op="Select by Weights (2)" to_port="example set input"/>
<connect from_op="Select by Weights (2)" from_port="example set output" to_op="Sample (Stratified) (2)" to_port="example set input"/>
<connect from_op="Sample (Stratified) (2)" from_port="example set output" to_port="out 1"/>
<portSpacing port="source_in 1" spacing="0"/>
<portSpacing port="source_in 2" spacing="0"/>
<portSpacing port="sink_out 1" spacing="0"/>
<portSpacing port="sink_out 2" spacing="0"/>
</process>
</operator>
<operator activated="true" class="concurrency:cross_validation" compatibility="9.6.000" expanded="true" height="145" name="Cross Validation" width="90" x="447" y="34">
<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="k_nn" compatibility="9.6.000" expanded="true" height="82" name="k-NN" width="90" x="112" y="34">
<parameter key="k" value="5"/>
<parameter key="weighted_vote" value="true"/>
<parameter key="measure_types" value="MixedMeasures"/>
<parameter key="mixed_measure" value="MixedEuclideanDistance"/>
<parameter key="nominal_measure" value="NominalDistance"/>
<parameter key="numerical_measure" value="EuclideanDistance"/>
<parameter key="divergence" value="GeneralizedIDivergence"/>
<parameter key="kernel_type" value="radial"/>
<parameter key="kernel_gamma" value="1.0"/>
<parameter key="kernel_sigma1" value="1.0"/>
<parameter key="kernel_sigma2" value="0.0"/>
<parameter key="kernel_sigma3" value="2.0"/>
<parameter key="kernel_degree" value="3.0"/>
<parameter key="kernel_shift" value="1.0"/>
<parameter key="kernel_a" value="1.0"/>
<parameter key="kernel_b" value="0.0"/>
</operator>
<connect from_port="training set" to_op="k-NN" to_port="training set"/>
<connect from_op="k-NN" 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="9.6.000" 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="9.6.000" expanded="true" height="82" name="Performance" width="90" x="179" y="34">
<parameter key="manually_set_positive_class" value="false"/>
<parameter key="main_criterion" value="first"/>
<parameter key="accuracy" value="true"/>
<parameter key="classification_error" value="false"/>
<parameter key="kappa" value="true"/>
<parameter key="AUC (optimistic)" value="false"/>
<parameter key="AUC" value="true"/>
<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"/>
<connect from_op="Performance" from_port="example set" to_port="test set results"/>
<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>
<connect from_op="Retrieve AirBnB Full" from_port="output" to_op="Subprocess" to_port="in 1"/>
<connect from_op="Subprocess" from_port="out 1" to_op="Cross Validation" to_port="example set"/>
<connect from_op="Cross Validation" from_port="model" to_port="result 1"/>
<connect from_op="Cross Validation" from_port="test result set" to_port="result 2"/>
<connect from_op="Cross Validation" from_port="performance 1" 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>