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Fraudes Proy Final

Tratamiento y preparación de datos
Undersampling controlado Relación 1:3
Clasificación - Decision Tree
Clasificación - Random Forest
Reglas de Asociación
Clustering (K-Means)
X-Aggregator
Decision Tree Predictor
Scorer
Arriba -> Fraudes Abajo -> No Fraudes
Row Splitter
8,213 fraudes + NO fraudes
Concatenate
X-Aggregator
Scorer
Random Forest Learner
Random Forest Predictor
Solo 100,000 registros
Row Sampler
Column Filter
X-Partitioner
Cluster Assigner
Color Manager
Con Z-Score
Normalizer
k-Means
Column Filter
Scatter Plot
GroupBy
fraudes.csv
CSV Reader
Statistics
Excluimos nameOrig y nameDest
Column Filter
Number -> Promedio String -> Moda
Missing Value
One to Many
Creamos balanceDifferenceOrig
Math Formula
Creamos balanceDifferenceDest
Math Formula
Association Rule Learner
Column Filter
Creamos amount_binned
Numeric Binner
Column Renamer
Data to Report (BIRT)
Create Bit Vector
One to Many
Statistics
Data to Report (BIRT)
MatrizConfDT
Data to Report (BIRT)
Column Filter
MatrizConfEF
Data to Report (BIRT)
Creamos percentBalanceUsed
Math Formula
Column Filter
Column Filter
AccuracyDT
Data to Report (BIRT)
Creamos largeTransactionNum
Rule Engine
Data to Report (BIRT)
Excluimos 'type'
Column Filter
24,639 NO fraudes
Row Sampler
Column Filter
Creamos isOriginEmpty
Rule Engine
Column Filter
Creamos isDestinationEmpty
Rule Engine
AccuracyRF
Data to Report (BIRT)
Decision Tree Learner
Para 'isFraud'
Number to String
X-Partitioner
Cluster
Data to Report (BIRT)
Shuffle

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: crisp
Created at: 2026-06-15
On NodePit since: 2026-06-20
Last update: 2026-06-24
Created with KNIME version: v5.11.0

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