Close Menu
    Trending
    • Designing a Machine Learning System: Part Five | by Mehrshad Asadi | Aug, 2025
    • Innovations in Artificial Intelligence That Are Changing Agriculture
    • Hundreds of thousands of Grok chats exposed in Google results
    • Workers Over 40 Are Turning to Side Hustles — Here’s Why
    • From Pixels to Perfect Replicas
    • In a first, Google has released data on how much energy an AI prompt uses
    • Mastering Fine-Tuning Foundation Models in Amazon Bedrock: A Comprehensive Guide for Developers and IT Professionals | by Nishant Gupta | Aug, 2025
    • The Key to Building Effective Corporate-Startup Partnerships
    AIBS News
    • Home
    • Artificial Intelligence
    • Machine Learning
    • AI Technology
    • Data Science
    • More
      • Technology
      • Business
    AIBS News
    Home»Machine Learning»Dominando Dados Desbalanceados: Qual Técnica de Balanceamento Vence na Detecção de Fraudes? | by samuel | Apr, 2025
    Machine Learning

    Dominando Dados Desbalanceados: Qual Técnica de Balanceamento Vence na Detecção de Fraudes? | by samuel | Apr, 2025

    Team_AIBS NewsBy Team_AIBS NewsApril 15, 2025No Comments1 Min Read
    Share Facebook Twitter Pinterest LinkedIn Tumblr Reddit Telegram Email
    Share
    Facebook Twitter LinkedIn Pinterest Email


    Visualização abstrata de um desbalanceamento de lessons

    Think about tentar encontrar uma agulha no palheiro. Esse é o desafio que os dados desbalanceados impõem aos modelos de Machine Studying. Em cenários como detecção de fraudes, diagnóstico de doenças raras ou previsão de falhas, a classe de interesse — os eventos que realmente importam — é uma minoria esmagadora. Sem o cuidado adequado, os modelos tendem a ignorar essa classe minoritária, entregando resultados decepcionantes justamente onde a precisão é mais crítica.

    Um exemplo clássico disso é o conjunto de dados Credit Card Fraud Detection, disponível no Kaggle. Nele, menos de 0,2% das transações são fraudulentas. Como construir um modelo que detecte essas agulhas no palheiro digital? Uma das estratégias mais populares é o balanceamento de dados. Mas com tantas opções — SMOTE, ADASYN, RandomOverSampler, RandomUnderSampler, Tomek Hyperlinks, ENN e métodos híbridos — , qual delas realmente faz a diferença?

    Para responder a essa pergunta, realizamos um experimento detalhado, comparando diversas técnicas de balanceamento e classificadores, usando o dataset de fraudes em cartões de crédito como campo de teste. Vamos compartilhar os resultados e as lições aprendidas para que você possa aplicá-las nos seus próprios projetos.



    Source link

    Share. Facebook Twitter Pinterest LinkedIn Tumblr Email
    Previous ArticleNVIDIA to Manufacture AI Supercomputers in U.S.
    Next Article Jack Dorsey Calls for End to Intellectual Property Law
    Team_AIBS News
    • Website

    Related Posts

    Machine Learning

    Designing a Machine Learning System: Part Five | by Mehrshad Asadi | Aug, 2025

    August 21, 2025
    Machine Learning

    Mastering Fine-Tuning Foundation Models in Amazon Bedrock: A Comprehensive Guide for Developers and IT Professionals | by Nishant Gupta | Aug, 2025

    August 21, 2025
    Machine Learning

    “How to Build an Additional Income Stream from Your Phone in 21 Days — A Plan You Can Copy” | by Zaczynam Od Zera | Aug, 2025

    August 21, 2025
    Add A Comment
    Leave A Reply Cancel Reply

    Top Posts

    Designing a Machine Learning System: Part Five | by Mehrshad Asadi | Aug, 2025

    August 21, 2025

    I Tried Buying a Car Through Amazon: Here Are the Pros, Cons

    December 10, 2024

    Amazon and eBay to pay ‘fair share’ for e-waste recycling

    December 10, 2024

    Artificial Intelligence Concerns & Predictions For 2025

    December 10, 2024

    Barbara Corcoran: Entrepreneurs Must ‘Embrace Change’

    December 10, 2024
    Categories
    • AI Technology
    • Artificial Intelligence
    • Business
    • Data Science
    • Machine Learning
    • Technology
    Most Popular

    Use This Framework to Successfully Integrate AI Into Your Business Operations

    December 11, 2024

    A Personal Reflection on Playlist Visibility and Inclusion on Suno | by MEHMET BAGBOZAN | May, 2025

    May 13, 2025

    How to Save on Capital Gains Taxes: Tax Loss Harvesting

    March 21, 2025
    Our Picks

    Designing a Machine Learning System: Part Five | by Mehrshad Asadi | Aug, 2025

    August 21, 2025

    Innovations in Artificial Intelligence That Are Changing Agriculture

    August 21, 2025

    Hundreds of thousands of Grok chats exposed in Google results

    August 21, 2025
    Categories
    • AI Technology
    • Artificial Intelligence
    • Business
    • Data Science
    • Machine Learning
    • Technology
    • Privacy Policy
    • Disclaimer
    • Terms and Conditions
    • About us
    • Contact us
    Copyright © 2024 Aibsnews.comAll Rights Reserved.

    Type above and press Enter to search. Press Esc to cancel.