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kn_​deeplearn_​010_​prepare_​adult_​dataset

Prepare the "adult" or "census-income" dataset for the use in deep learning nodes and models.

Prepare the "adult" or "census-income" dataset for the use in deep learning nodes and models.
Convert numbers to double and do a label enconding on the string variables with the help of SQLite. Yes, you will have to be careful with that :-)

please download the complete DeepLearning (Keras, Tensorflow, H2O.ai) Workflow group:
https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_deeplearning_keras_tensorflow_classification~G8jl-DTMCBqoxyB9/

adapted from: https://kni.me/w/Cm0lqIKkvThyHAD-

Prepare the "adult" or "census-income" dataset for the use in deep learning nodes and models.Convert numbers to double and do a label enconding on the string variables with the help of SQLite. Yes, you will have to be careful with that :-)please download the complete DeepLearning (Keras, Tensorflow, H2O.ai) Workflow group:https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_deeplearning_keras_tensorflow_classification~G8jl-DTMCBqoxyB9/adapted from: https://kni.me/w/Cm0lqIKkvThyHAD- this is where themagic happens of label encodingReplace edcuationwith integer valuesReplace missingvalues 30% for validation70 % for testing 70% for training 30 % lower../data/adult.csv../data/Education_Dictionary.xlsxDictionary table to rank educationnumeric_cols$income$ = ">50K" =>"1"TRUE =>"0"create Target^(?!income$).*get rid of the"-"knime://knime.workflow/../data/my_databse.sqlite=> can be done in memory like inthis exampledeep_001_trainingdeep_001_trainingDROP TABLE IF EXISTS adult_001_training;deep_001_traininghow to handle thenumeric variableswith CAST commands!!! careful in this examples negativevalues are handeled as 0 (zero)../model/nvl_numeric_sql_sqlite.tablenvl_numericdeep_001_trainingstring_cols$${Sspark_label_encoder}$$ , $${Snvl_numeric}$$deep_001_trainingdeep_001_trainingZ-Score../model/normalize.pmml../model/normalize.pmml../data/deep_001_training.table../data/deep_005_test.table../data/deep_009_validate.tabletestvalidateSQLite LabelEncoder Cell Replacer Missing Value Partitioning Partitioning File Reader Excel Reader Column Filter Rule Engine Column Filter Column Rename SQLite Connector DB Table Remover DB Table Creator DB SQL Executor DB Writer numeric NVL Table Reader Table Rowto Variable DB Query Column Filter Merge Variables DB Reader Normalizer (PMML) PMML Writer PMML Reader Table Writer Table Writer Table Writer deep_005_test deep_009_validate Prepare the "adult" or "census-income" dataset for the use in deep learning nodes and models.Convert numbers to double and do a label enconding on the string variables with the help of SQLite. Yes, you will have to be careful with that :-)please download the complete DeepLearning (Keras, Tensorflow, H2O.ai) Workflow group:https://hub.knime.com/mlauber71/spaces/Public/latest/kn_example_deeplearning_keras_tensorflow_classification~G8jl-DTMCBqoxyB9/adapted from: https://kni.me/w/Cm0lqIKkvThyHAD- this is where themagic happens of label encodingReplace edcuationwith integer valuesReplace missingvalues 30% for validation70 % for testing70% for training 30 % lower../data/adult.csv../data/Education_Dictionary.xlsxDictionary table to rank educationnumeric_cols$income$ = ">50K" =>"1"TRUE =>"0"create Target^(?!income$).*get rid of the"-"knime://knime.workflow/../data/my_databse.sqlite=> can be done in memory like inthis exampledeep_001_trainingdeep_001_trainingDROP TABLE IF EXISTS adult_001_training;deep_001_traininghow to handle thenumeric variableswith CAST commands!!! careful in this examples negativevalues are handeled as 0 (zero)../model/nvl_numeric_sql_sqlite.tablenvl_numericdeep_001_trainingstring_cols$${Sspark_label_encoder}$$ , $${Snvl_numeric}$$deep_001_trainingdeep_001_trainingZ-Score../model/normalize.pmml../model/normalize.pmml../data/deep_001_training.table../data/deep_005_test.table../data/deep_009_validate.tabletestvalidateSQLite LabelEncoder Cell Replacer Missing Value Partitioning Partitioning File Reader Excel Reader Column Filter Rule Engine Column Filter Column Rename SQLite Connector DB Table Remover DB Table Creator DB SQL Executor DB Writer numeric NVL Table Reader Table Rowto Variable DB Query Column Filter Merge Variables DB Reader Normalizer (PMML) PMML Writer PMML Reader Table Writer Table Writer Table Writer deep_005_test deep_009_validate

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: m_lauber
Created at: 2021-12-28
On NodePit since: 2021-12-29
Last update: 2024-04-27
Created with KNIME version: v4.5.0
Tags: deep learningdatapreparationsqlitelabel encoding

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