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credit scoring by neural network

import the csv fileencode the categorical variablesNormalize the dataTrain and cross validate the neural networkNode 5Train and cross validate the decision tree classifierTrain and cross validate the svmNode 8Node 9table with accuracyand model nametable with accuracyand model nametable with accuracyand model nameNode 39Node 40Node 41Node 42Pick up the best modelCSV Reader Category To Number Normalizer Metanode 1 : 1 Scorer Metanode 1 : 1 Metanode 1 : 1 Scorer Scorer Metanode 1 : 1 Metanode 1 : 1 Metanode 1 : 1 Apply the modelon all data Apply the modelon all data Apply the modelon all data Cross Joiner Cross Joiner Cross Joiner Metanode Row Filter Cell To PMML PMML Writer visualization import the csv fileencode the categorical variablesNormalize the dataTrain and cross validate the neural networkNode 5Train and cross validate the decision tree classifierTrain and cross validate the svmNode 8Node 9table with accuracyand model nametable with accuracyand model nametable with accuracyand model nameNode 39Node 40Node 41Node 42Pick up the best modelCSV Reader Category To Number Normalizer Metanode 1 : 1 Scorer Metanode 1 : 1 Metanode 1 : 1 Scorer Scorer Metanode 1 : 1 Metanode 1 : 1 Metanode 1 : 1 Apply the modelon all data Apply the modelon all data Apply the modelon all data Cross Joiner Cross Joiner Cross Joiner Metanode Row Filter Cell To PMML PMML Writer visualization

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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: 91726
Created at: 2023-02-17
On NodePit since: 2023-02-18
Last update: 2024-04-24
Created with KNIME version: v4.7.1

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