#FeatureSelection

📌 Video 15/100 — Covarianza y correlación: Pearson, Spearman y la trampa que engañó a Google y a eBay eBay gastó decenas de millones en publicidad creyendo que los clics causaban ventas. Un experimento demostró que obtenían 25 centavos por cada dólar invertido. El problema: confundieron…

Curse of dimensionality reminds us to think carefully about feature selection. More isn’t always better. Use a feature selection curve.

Curse of dimensionality reminds us to think carefully about feature selection. More isn’t always better. Use a feature selection curve. #datascience #machinelearning #curseofdimensionality #featureselection Curse of dimensionality reminds us to think carefully about feature selection. More isn’t…

Feature Selection Optimization for Machine Learning Malware Detection This research paper investigates how machine learning can enhance malware detection by utilizing feature selection to identify the most critical program characteristics. The authors propose a multi-step framework involving data…

Akurasi model klasifikasi yang rendah dapat disebabkan oleh beberapa faktor, seperti dataset yang tidak seimbang sehingga model hanya fokus pada kelas mayoritas, kualitas data yang buruk dengan adanya nilai kosong atau label salah, fitur yang tidak relevan atau terlalu banyak noise, model yang…

Si la correlación falla, la información mutua revela relaciones no lineales. Aprende qué mide, cómo estimarla y cómo validarla para decidir con confianza.

One of my favorite methods for feature selection is recursive feature elimination. It's very easy to do and a starting data scientist can code this up. This is a starting point, feature selection is a much larger topic. I did a more sophisticated version of this at DataRobot that I called Feature…

mimin mau ingetin lagi alur kerja data yang bener. Banyak yang pengen cepet-cepet dapet hasil (Step 4), tapi males ngelewatin Step 1 dan 2. Padahal, kalau 'pondasinya' berantakan, hasil akhirnya nggak bakal bisa dipercaya. 📉 Ibarat mau masak, Step 1-3 itu persiapan bahan. Kalau bahannya segar dan…

Learn essential feature selection methods for improving ML model performance. Explore filter, wrapper, and embedded techniques to identify the most relevant features. Discover how to use correlation analysis, variance threshold, recursive feature elimination, and more to optimize your datasets…

Bisa jadi model kamu lagi 'kebanyakan beban'! 📉 Feature Selection itu ibarat lagi packing buat naik gunung. Kamu nggak bakal bawa sofa atau TV kan? Kamu cuma bawa barang yang beneran dibutuhin biar perjalanannya cepet dan sampai tujuan dengan selamat. Di dunia data, milih variabel yang 'pas' itu…

Think your fancy machine learning model with thousands of features is impressive? Think again! Our founder dropped some knowledge at PyData 2017 about why simpler models might be the real MVPs in finance. Here's the breakdown: Simpler is (Often) Better. Why? 👇 ▶️ Easy Implementation: Developers…

Feature Selection in Python using Information Gain and Mutual Information Explore advanced feature selection techniques using Python and scikit-learn. Starting from basic concepts like entropy and information gain, moving to practical implementations and real-world examples. Focus on both…

Let’s see how Lasso Regression (L1 Regularization) simplifies our model by shrinking unnecessary coefficients to zero! ⚡ 🧠 Today’s demo uses synthetic data — perfect to visualize how Lasso selects only the most important features. 📉 Watch how the line adjusts as alpha increases — less noise, more…

Day 33: Feature Selection & Scaling! 🚀 Simplifying models, improving speed, and making data work smarter. Keep learning, keep growing!

Learning the theory is just the beginning. You master these amazing models, but then you get your first dataset, and it's nothing like the clean examples from beginner courses. So, what do you do when reality doesn't match the textbook? Get hands-on experience! 📌 Save this for later if you’re in a…

Explore how regularization techniques in Python can lead to zero coefficients, enhancing model performance and interpretability. Learn about L1, L2, and Elastic Net regularization, their impact on feature selection, and practical implementation using scikit-learn. #MachineLearning #Python…

📊 Belajar Pemilihan Variabel dalam Analisis Regresi Pemilihan variabel merupakan tahapan penting dalam analisis data untuk menentukan variabel mana yang relevan digunakan dalam model. Dengan pemilihan variabel yang tepat, model regresi dapat menjadi lebih baik, efisien, dan mudah…

🎯 Day 29: Feature Selection — Smart Learning ko Beginning! ✨ Aaja ko topic Feature Selection ho. Dataset ma dherai kura huna sakchhan, tara ML model ko lagi sabai important hudainan. Junk data lai hataunu ra model lai "Smart" banaunu nai Feature Selection ho. Exam ko syllabus jasto—sabai book…

Day 32 📈 Feature Selection in Machine Learning