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Logistic Regression Limited Data
nathaliejoy
Member Posts: 7 
Contributor II
I want to Use Logistic Regression in Rapidminer but I have less than 100 data. I am currently working in an Education Data Mining Project.I only have 94 rows total and this is all I have, is it okey to repeat the rows?
I want to know relationship between the National Achievement Test and their Grades and the likelihood they are going to pass or fail the exam.
The problem is that I have small number of row. Help me what to do.The following is my xml code:
<?xml version="1.0" encoding="UTF-8"?><process version="9.7.001">
<context>
<input/>
<output/>
<macros/>
</context>
<operator activated="true" class="process" compatibility="9.7.001" 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="read_excel" compatibility="9.7.001" expanded="true" height="68" name="Read Excel" width="90" x="45" y="34">
<parameter key="excel_file" value="D:\MyDocuments\CMUFiles\RESEARCH AND EXTENSION\SHs Performance NAT in Bukidnon\ExcelSubjectTemplate\ABM.xlsx"/>
<parameter key="sheet_selection" value="sheet number"/>
<parameter key="sheet_number" value="1"/>
<parameter key="imported_cell_range" value="A1"/>
<parameter key="encoding" value="SYSTEM"/>
<parameter key="first_row_as_names" value="true"/>
<list key="annotations"/>
<parameter key="date_format" value=""/>
<parameter key="time_zone" value="SYSTEM"/>
<parameter key="locale" value="English (United States)"/>
<parameter key="read_all_values_as_polynominal" value="false"/>
<list key="data_set_meta_data_information">
<parameter key="0" value="Name.true.polynominal.attribute"/>
<parameter key="1" value="ELS-G11-Q1.true.integer.attribute"/>
<parameter key="2" value="ELS-G11-Q2.true.integer.attribute"/>
<parameter key="3" value="PS-G11-Q3.true.integer.attribute"/>
<parameter key="4" value="PS-G11-Q4.true.integer.attribute"/>
<parameter key="5" value="SC-PS-NAT.true.real.attribute"/>
<parameter key="6" value="SC-PS-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="7" value="SC-IL-NAT.true.real.attribute"/>
<parameter key="8" value="SC-IL-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="9" value="SC-CT-NAT.true.real.attribute"/>
<parameter key="10" value="SC-CT-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="11" value="Total-MPS-Science.true.real.attribute"/>
<parameter key="12" value="Overall-Remarks-Science.true.polynominal.attribute"/>
<parameter key="13" value="PD-G11-Q1.true.integer.attribute"/>
<parameter key="14" value="PD-G11-Q2.true.integer.attribute"/>
<parameter key="15" value="UCSP-G11-Q1.true.integer.attribute"/>
<parameter key="16" value="UCSP-G11-Q2.true.integer.attribute"/>
<parameter key="17" value="2CLPW-G12-Q1.true.integer.attribute"/>
<parameter key="18" value="2CLPW-G12-Q2.true.integer.attribute"/>
<parameter key="19" value="SS-PS-NAT.true.real.attribute"/>
<parameter key="20" value="SS-PS-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="21" value="SS-IL-NAT.true.real.attribute"/>
<parameter key="22" value="SS-IL-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="23" value="SS-CT-NAT.true.real.attribute"/>
<parameter key="24" value="SS-CT-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="25" value="Total-MPS.true.real.attribute"/>
<parameter key="26" value="Overall-Remarks-Social-Science.true.polynominal.attribute"/>
<parameter key="27" value="Ph-G12-Q1.true.integer.attribute"/>
<parameter key="28" value="Ph-G12-Q2.true.integer.attribute"/>
<parameter key="29" value="Ph-PS-NAT.true.real.attribute"/>
<parameter key="30" value="Ph-PS-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="31" value="Ph-IL-NAT.true.real.attribute"/>
<parameter key="32" value="Ph-IL-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="33" value="Ph-CT-NAT.true.real.attribute"/>
<parameter key="34" value="Ph-CT-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="35" value="Total-MPS-Philosophy.true.real.attribute"/>
<parameter key="36" value="Overall-Remarks-Philosophy.true.polynominal.attribute"/>
<parameter key="37" value="AL.true.polynominal.attribute"/>
<parameter key="38" value="GM-G11-Q1.true.integer.attribute"/>
<parameter key="39" value="GM-G11-Q2.true.integer.attribute"/>
<parameter key="40" value="M-PS-NAT.true.real.attribute"/>
<parameter key="41" value="M-PS-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="42" value="M-IL-NAT.true.real.attribute"/>
<parameter key="43" value="M-IL-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="44" value="M-CT-NAT.true.real.attribute"/>
<parameter key="45" value="M-CT-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="46" value="Total-MPS-Math.true.real.attribute"/>
<parameter key="47" value="Overall-Remarks-Math.true.polynominal.attribute"/>
<parameter key="48" value="OC-G11-Q1.true.integer.attribute"/>
<parameter key="49" value="OC-G11-Q2.true.integer.attribute"/>
<parameter key="50" value="F-G11-Q1.true.integer.attribute"/>
<parameter key="51" value="F-G11-Q2.true.integer.attribute"/>
<parameter key="52" value="EAPP-G11-Q1.true.integer.attribute"/>
<parameter key="53" value="EAPP-G11-Q2.true.integer.attribute"/>
<parameter key="54" value="RWS-G11-Q3.true.integer.attribute"/>
<parameter key="55" value="RWS-G11-Q4.true.integer.attribute"/>
<parameter key="56" value="F-G11-Q3.true.integer.attribute"/>
<parameter key="57" value="F-G11-Q4.true.integer.attribute"/>
<parameter key="58" value="LC-PS-NAT.true.real.attribute"/>
<parameter key="59" value="LC-PS-NAT-Rem.true.polynominal.attribute"/>
<parameter key="60" value="LC-IL-NAT.true.real.attribute"/>
<parameter key="61" value="LC-IL-NAT-Rem.true.polynominal.attribute"/>
<parameter key="62" value="LC-CT-NAT.true.real.attribute"/>
<parameter key="63" value="LC-CT-NAT-Rem.true.real.attribute"/>
<parameter key="64" value="Total-MPS-LC.true.real.attribute"/>
<parameter key="65" value="overall-remarks-LC.true.polynominal.attribute"/>
<parameter key="66" value="ICT-G11-Q3.true.integer.attribute"/>
<parameter key="67" value="ICT-G11-Q4.true.integer.attribute"/>
<parameter key="68" value="MIL-G12-Q1.true.integer.attribute"/>
<parameter key="69" value="MIL-G12-Q2.true.integer.attribute"/>
<parameter key="70" value="MIL-PS-NAT.true.real.attribute"/>
<parameter key="71" value="MIL-PS-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="72" value="MIL-IL-NAT.true.real.attribute"/>
<parameter key="73" value="MIL-IL-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="74" value="MIL-CT-NAT.true.real.attribute"/>
<parameter key="75" value="MIL-CT-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="76" value="Total-MPS-MIL.true.real.attribute"/>
<parameter key="77" value="Overall-Remarks-MIL.true.polynominal.attribute"/>
<parameter key="78" value="Arts-G12-Q1.true.integer.attribute"/>
<parameter key="79" value="Arts-G12-Q2.true.integer.attribute"/>
<parameter key="80" value="Arts-PS-NAT.true.real.attribute"/>
<parameter key="81" value="Arts-PS-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="82" value="ARTS-IL-NAT.true.real.attribute"/>
<parameter key="83" value="ARTS-IL-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="84" value="ARTS-CT-NAT.true.real.attribute"/>
<parameter key="85" value="ARTS-CT-NAT-Remarks.true.polynominal.attribute"/>
<parameter key="86" value="Total-MPS-Hummanities.true.real.attribute"/>
<parameter key="87" value="Overall-Remarks-Humanities.true.polynominal.attribute"/>
<parameter key="88" value="PS-MPS-All-Subject.true.real.attribute"/>
<parameter key="89" value="PS-MPS-All-Subject-Remarks.true.polynominal.attribute"/>
<parameter key="90" value="CT-MPS-All-Subject.true.real.attribute"/>
<parameter key="91" value="CT-MPS-All-Subject-Remarks.true.polynominal.attribute"/>
<parameter key="92" value="IL-MPS-All-Subject.true.real.attribute"/>
<parameter key="93" value="IL-MPS-All-Subject-Remarks.true.polynominal.attribute"/>
<parameter key="94" value="NAT-Grade.true.real.attribute"/>
<parameter key="95" value="NAT-Grade-Remarks.true.polynominal.attribute"/>
</list>
<parameter key="read_not_matching_values_as_missings" value="true"/>
<parameter key="datamanagement" value="double_array"/>
<parameter key="data_management" value="auto"/>
</operator>
<operator activated="true" class="subprocess" compatibility="9.7.001" expanded="true" height="82" name="Subprocess" width="90" x="179" y="34">
<process expanded="true">
<operator activated="true" class="replace_missing_values" compatibility="9.7.001" expanded="true" height="103" name="Replace Missing Values" width="90" x="45" y="34">
<parameter key="return_preprocessing_model" value="false"/>
<parameter key="create_view" value="false"/>
<parameter key="attribute_filter_type" value="all"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value=""/>
<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="false"/>
<parameter key="default" value="average"/>
<list key="columns"/>
</operator>
<operator activated="true" class="generate_id" compatibility="9.7.001" expanded="true" height="82" name="Generate ID" width="90" x="246" y="34">
<parameter key="create_nominal_ids" value="false"/>
<parameter key="offset" value="0"/>
</operator>
<operator activated="true" class="select_attributes" compatibility="9.7.001" expanded="true" height="82" name="Select Attributes" width="90" x="514" y="34">
<parameter key="attribute_filter_type" value="subset"/>
<parameter key="attribute" value=""/>
<parameter key="attributes" value="2CLPW-G12-Q1|2CLPW-G12-Q2|Arts-G12-Q1|Arts-G12-Q2|EAPP-G11-Q1|EAPP-G11-Q2|ELS-G11-Q1|ELS-G11-Q2|F-G11-Q1|F-G11-Q2|F-G11-Q3|F-G11-Q4|GM-G11-Q1|GM-G11-Q2|ICT-G11-Q3|ICT-G11-Q4|id|MIL-G12-Q1|MIL-G12-Q2|NAT-Grade-Remarks|OC-G11-Q1|OC-G11-Q2|PD-G11-Q1|PD-G11-Q2|Ph-G12-Q1|Ph-G12-Q2|PS-G11-Q3|PS-G11-Q4|RWS-G11-Q3|RWS-G11-Q4|UCSP-G11-Q1|UCSP-G11-Q2"/>
<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="false"/>
</operator>
<connect from_port="in 1" to_op="Replace Missing Values" to_port="example set input"/>
<connect from_op="Replace Missing Values" from_port="example set output" to_op="Generate ID" to_port="example set input"/>
<connect from_op="Generate ID" from_port="example set output" to_op="Select Attributes" to_port="example set input"/>
<connect from_op="Select Attributes" 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="set_role" compatibility="9.7.001" expanded="true" height="82" name="Set Role" width="90" x="313" y="34">
<parameter key="attribute_name" value="id"/>
<parameter key="target_role" value="batch"/>
<list key="set_additional_roles">
<parameter key="NAT-Grade-Remarks" value="label"/>
</list>
</operator>
<operator activated="true" class="optimize_selection_evolutionary" compatibility="9.7.001" expanded="true" height="103" name="Optimize Selection (Evolutionary)" width="90" x="514" y="34">
<parameter key="use_exact_number_of_attributes" value="false"/>
<parameter key="restrict_maximum" value="false"/>
<parameter key="min_number_of_attributes" value="1"/>
<parameter key="max_number_of_attributes" value="1"/>
<parameter key="exact_number_of_attributes" value="1"/>
<parameter key="initialize_with_input_weights" value="false"/>
<parameter key="population_size" value="5"/>
<parameter key="maximum_number_of_generations" value="30"/>
<parameter key="use_early_stopping" value="false"/>
<parameter key="generations_without_improval" value="2"/>
<parameter key="normalize_weights" value="true"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<parameter key="user_result_individual_selection" value="false"/>
<parameter key="show_population_plotter" value="false"/>
<parameter key="plot_generations" value="10"/>
<parameter key="constraint_draw_range" value="false"/>
<parameter key="draw_dominated_points" value="true"/>
<parameter key="maximal_fitness" value="Infinity"/>
<parameter key="selection_scheme" value="tournament"/>
<parameter key="tournament_size" value="0.25"/>
<parameter key="start_temperature" value="1.0"/>
<parameter key="dynamic_selection_pressure" value="true"/>
<parameter key="keep_best_individual" value="false"/>
<parameter key="save_intermediate_weights" value="false"/>
<parameter key="intermediate_weights_generations" value="10"/>
<parameter key="p_initialize" value="0.5"/>
<parameter key="p_mutation" value="-1.0"/>
<parameter key="p_crossover" value="0.5"/>
<parameter key="crossover_type" value="uniform"/>
<process expanded="true">
<operator activated="true" class="concurrency:cross_validation" compatibility="9.7.001" expanded="true" height="145" name="Cross Validation" width="90" x="112" 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="linear sampling"/>
<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="polynomial_by_binomial_classification" compatibility="9.7.001" expanded="true" height="82" name="Polynominal by Binominal Classification" width="90" x="112" y="34">
<parameter key="classification_strategies" value="1 against all"/>
<parameter key="random_code_multiplicator" value="2.0"/>
<parameter key="use_local_random_seed" value="false"/>
<parameter key="local_random_seed" value="1992"/>
<process expanded="true">
<operator activated="true" class="h2o:logistic_regression" compatibility="9.7.001" expanded="true" height="124" name="Logistic Regression" width="90" x="112" y="34">
<parameter key="solver" value="AUTO"/>
<parameter key="reproducible" value="false"/>
<parameter key="maximum_number_of_threads" value="4"/>
<parameter key="use_regularization" value="false"/>
<parameter key="lambda_search" value="false"/>
<parameter key="number_of_lambdas" value="0"/>
<parameter key="lambda_min_ratio" value="0.0"/>
<parameter key="early_stopping" value="true"/>
<parameter key="stopping_rounds" value="3"/>
<parameter key="stopping_tolerance" value="0.001"/>
<parameter key="standardize" value="true"/>
<parameter key="non-negative_coefficients" value="false"/>
<parameter key="add_intercept" value="true"/>
<parameter key="compute_p-values" value="true"/>
<parameter key="remove_collinear_columns" value="true"/>
<parameter key="missing_values_handling" value="MeanImputation"/>
<parameter key="max_iterations" value="0"/>
<parameter key="max_runtime_seconds" value="0"/>
</operator>
<connect from_port="training set" to_op="Logistic Regression" to_port="training set"/>
<connect from_op="Logistic Regression" from_port="model" to_port="model"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
</process>
</operator>
<connect from_port="training set" to_op="Polynominal by Binominal Classification" to_port="training set"/>
<connect from_op="Polynominal by Binominal Classification" from_port="model" to_port="model"/>
<connect from_op="Polynominal by Binominal Classification" from_port="example set" to_port="through 1"/>
<portSpacing port="source_training set" spacing="0"/>
<portSpacing port="sink_model" spacing="0"/>
<portSpacing port="sink_through 1" spacing="0"/>
<portSpacing port="sink_through 2" spacing="0"/>
</process>
<process expanded="true">
<operator activated="true" class="apply_model" compatibility="9.7.001" 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_classification" compatibility="9.7.001" 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="weighted_mean_recall" value="false"/>
<parameter key="weighted_mean_precision" value="false"/>
<parameter key="spearman_rho" value="false"/>
<parameter key="kendall_tau" value="false"/>
<parameter key="absolute_error" value="false"/>
<parameter key="relative_error" value="false"/>
<parameter key="relative_error_lenient" value="false"/>
<parameter key="relative_error_strict" value="false"/>
<parameter key="normalized_absolute_error" value="false"/>
<parameter key="root_mean_squared_error" value="false"/>
<parameter key="root_relative_squared_error" value="false"/>
<parameter key="squared_error" value="false"/>
<parameter key="correlation" value="false"/>
<parameter key="squared_correlation" value="false"/>
<parameter key="cross-entropy" value="false"/>
<parameter key="margin" value="false"/>
<parameter key="soft_margin_loss" value="false"/>
<parameter key="logistic_loss" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
<list key="class_weights"/>
</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="source_through 2" 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="9.7.001" expanded="true" height="82" name="Apply Model (2)" width="90" x="380" y="34">
<list key="application_parameters"/>
<parameter key="create_view" value="false"/>
</operator>
<operator activated="true" class="set_role" compatibility="9.7.001" expanded="true" height="82" name="Set Role (2)" width="90" x="514" y="34">
<parameter key="attribute_name" value="NAT-Grade-Remarks"/>
<parameter key="target_role" value="label"/>
<list key="set_additional_roles">
<parameter key="prediction(NAT-Grade-Remarks)" value="prediction"/>
</list>
</operator>
<operator activated="true" class="performance_classification" compatibility="9.7.001" expanded="true" height="82" name="Performance (2)" width="90" x="648" 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="weighted_mean_recall" value="false"/>
<parameter key="weighted_mean_precision" value="false"/>
<parameter key="spearman_rho" value="false"/>
<parameter key="kendall_tau" value="false"/>
<parameter key="absolute_error" value="false"/>
<parameter key="relative_error" value="false"/>
<parameter key="relative_error_lenient" value="false"/>
<parameter key="relative_error_strict" value="false"/>
<parameter key="normalized_absolute_error" value="false"/>
<parameter key="root_mean_squared_error" value="false"/>
<parameter key="root_relative_squared_error" value="false"/>
<parameter key="squared_error" value="false"/>
<parameter key="correlation" value="false"/>
<parameter key="squared_correlation" value="false"/>
<parameter key="cross-entropy" value="false"/>
<parameter key="margin" value="false"/>
<parameter key="soft_margin_loss" value="false"/>
<parameter key="logistic_loss" value="false"/>
<parameter key="skip_undefined_labels" value="true"/>
<parameter key="use_example_weights" value="true"/>
<list key="class_weights"/>
</operator>
<connect from_port="example set" to_op="Cross Validation" to_port="example set"/>
<connect from_op="Cross Validation" from_port="model" to_op="Apply Model (2)" to_port="model"/>
<connect from_op="Cross Validation" from_port="example set" to_op="Apply Model (2)" to_port="unlabelled data"/>
<connect from_op="Apply Model (2)" from_port="labelled data" to_op="Set Role (2)" to_port="example set input"/>
<connect from_op="Set Role (2)" from_port="example set output" to_op="Performance (2)" to_port="labelled data"/>
<connect from_op="Performance (2)" from_port="performance" to_port="performance"/>
<portSpacing port="source_example set" spacing="0"/>
<portSpacing port="source_through 1" spacing="0"/>
<portSpacing port="sink_performance" spacing="0"/>
</process>
</operator>
<connect from_op="Read Excel" from_port="output" to_op="Subprocess" to_port="in 1"/>
<connect from_op="Subprocess" from_port="out 1" to_op="Set Role" to_port="example set input"/>
<connect from_op="Set Role" from_port="example set output" to_op="Optimize Selection (Evolutionary)" to_port="example set in"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="example set out" to_port="result 1"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="weights" to_port="result 2"/>
<connect from_op="Optimize Selection (Evolutionary)" from_port="performance" 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>
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hbajpai
Member Posts: 102 
Unicorn
@nathaliejoy
I would not recommend repeating rows as they do not have any new information and will not help in your model development. Utilizing GLM and other simpler model should be the way to go. Also, if you can create some extra features that can help with modelling.Best,
Harshit1
