Icon

Bank Loan Modeling with Auto Categorical Features Embedding

Bank Loan Modeling with Auto Categorical Features Embedding
Without Auto Categorical Features Embedding With Auto Categorical Features Embedding # Last amended: 06th Oct, 2021# Data Source: Kaggle: https://www.kaggle.com/dataforyou/bankloanWorkflow demonstrates use of Auto Categorical Features Embedding node Min/Maxnormalizationtransformtarget: defualt_on_payment& Dependents, Num_CC5000 X 2216: categorical5: numeric5-folds Auto CategoricalFeatures Embedding Normalizer Constant ValueColumn Filter Number To String LogisticRegression Learner Logistic RegressionPredictor Scorer LogisticRegression Learner Logistic RegressionPredictor Scorer Table Reader X-Partitioner X-Aggregator Partitioning Without Auto Categorical Features Embedding With Auto Categorical Features Embedding # Last amended: 06th Oct, 2021# Data Source: Kaggle: https://www.kaggle.com/dataforyou/bankloanWorkflow demonstrates use of Auto Categorical Features Embedding node Min/Maxnormalizationtransformtarget: defualt_on_payment& Dependents, Num_CC5000 X 2216: categorical5: numeric5-foldsAuto CategoricalFeatures Embedding Normalizer Constant ValueColumn Filter Number To String LogisticRegression Learner Logistic RegressionPredictor Scorer LogisticRegression Learner Logistic RegressionPredictor Scorer Table Reader X-Partitioner X-Aggregator Partitioning

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: ashok
Created at: 2021-09-17
On NodePit since: 2021-09-18
Last update: 2024-12-17
Created with KNIME version: v4.4.1
Tags: Bank Loan defaultFeature transformationLogistic Regression

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!