---
title: "Discussion on \"From Decision Trees to XGBoost: A Practical Comparison on Breast Cancer Dataset\" | Hashnode"
description: "Discussion on \"From Decision Trees to XGBoost: A Practical Comparison on Breast Cancer Dataset\". 🧠 Introduction\nIn machine learning, choosing the right model can significantly impact performance. While simple models like Decision Trees are easy to interpret, advanced ensemble techniques like Ran"
url: "https://hashnode.com/posts/from-decision-trees-to-xgboost-a-practical-comparison-on-breast-cancer-dataset/69bc2ba3b238fd45a31bdf38"
---

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# [From Decision Trees to XGBoost: A Practical Comparison on Breast Cancer Dataset](https://krish27.hashnode.dev/from-decision-trees-to-xgboost-a-practical-comparison-on-breast-cancer-dataset?utm_source=hashnode&utm_medium=feed)

🧠 Introduction In machine learning, choosing the right model can significantly impact performance. While simple models like Decision Trees are easy to interpret, advanced ensemble techniques like Ran

Mar 19 · 4 min read · krish27.hashnode.dev  
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## Written by

[Krishnat Ramchandra Hogale](https://hashnode.com/@krish27)

@krish27 · Pune

  
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DevOps and Automation Engineer

I am an Information Technology Analyst at NTT DATA North America, where I specialize in DevOps, automation testing, and cloud-native deployments. Over the past 3 years, I’ve built CI/CD pipelines, test automation frameworks, and Generative AI solutions that help organizations streamline their workflows and improve efficiency. My Background - I studied at the Indian Institute of Technology, Patna. - Since July 2022, I’ve been contributing to projects at NTT DATA North America. My Skills - Automation Testing: REST API and UI automation using Java, Selenium, REST Assured, TestNG. - DevOps Tools: GitHub Actions, Jenkins, Docker, Terraform, Kubernetes, Azure DevOps, AWS. - Programming: Proficient in Python and Java. - Cloud & Microservices: Deploying Python-based applications on AWS EC2, integrating with MySQL and OpenAI APIs. - Monitoring & Performance: Experienced with Datadog, Grafana, JMeter, Gatling. My Achievements - Improved test efficiency by 40% through automation frameworks. - Led Generative AI initiatives, including prompt engineering, LangChain workflows, and retrieval-augmented generation (RAG) systems. - Enhanced application performance by 10% through API call caching and load testing. My Professional Presence I am active on LinkedIn, where I have over 4,000 followers and 500+ connections

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