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TP_​APP_​PrestamosFinal

Leemos CSV
CSV Reader
Quitamos el Loan_ID
Column Filter
Missing Values de todomenos Credit_History
Missing Value
Missing Value (Apply)
Distribución ApplicantIncome
Histogram
Credit_History
Pie Chart
Rank Correlation
Credit_history luego de missing values
Pie Chart
Concateno los datasetspara continuar el análisis
Concatenate
String to Number
Gender
Pie Chart
Zona
Pie Chart
Decision Tree Learner
Unpivot
ROC Curve
Heatmap
Box Plot
Dependents
Rule Engine
Chart Dependents agrupado
Pie Chart
Scatter Plot Matrix
Dependents antes de agrupacion
Pie Chart
Married YES => 1
Rule Engine
Variables dummies para Property_area
One to Many
Loan_Status YES => 1
Rule Engine
Modelo que saque patronesdel dataset sin missing values
Random Forest Learner
Genero_femenino => 1
Rule Engine
Column Renamer
Dividir en dos tablas según missing values de Credit_History
Rule-based Row Splitter
Education Graduate => 1
Rule Engine
Self_Employed YES => 1
Rule Engine
Convierto a String Credit_History
Number to String
Heatmap
Column Renamer
Unpivot
Linear Correlation
Ejecutar prediccióny llenar missing values
Random Forest Predictor
Column Filter

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: Ariana
Created at: 2026-04-02
On NodePit since: 2026-04-12
Last update: 2026-04-12
Created with KNIME version: v5.8.3

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