Decision Trees,Resampling & Evaluation Metrics : ONE-SHOT GATE DA | Concept to Combat Session 4 🔥 скачать в хорошем качестве

Decision Trees,Resampling & Evaluation Metrics : ONE-SHOT GATE DA | Concept to Combat Session 4 🔥

Welcome to Session 4 of the Concept to Combat series! This is your ultimate one-stop resource for mastering some of the most high-weight and frequently tested topics in the GATE DA Machine Learning syllabus: Decision Trees, Resampling Methods, and Evaluation Metrics. What you'll learn: In this session, we will do a recap of the concepts and then go in deep dive for extensive practice of GATE-level problems. We don’t just stop at the theory; we ensure you can apply every formula and geometric intuition to solve complex questions under pressure. 📘 Click the link below to download all session PDFs: https://drive.google.com/drive/folder... Join our Communities for Notes: Telegram: https://t.me/ManojGateDA Discord:   / discord   ML Module Schedule: Jan 20 – Feb 1. Subscribe to TAAI- Manoj Kumar to join the combat live! Jump to Topics: [00:00:00] Session Introduction and Overview [00:01:50] Soft Margin SVM: Transition from Hard Margin [00:05:32] Understanding the Slack Variable (Zeta) [00:09:27] The C Hyperparameter and Misclassification Trade-offs [00:17:21] SVM Regularization: Bias-Variance Trade-off [00:24:35] Introduction to Hinge Loss [00:27:36] Log Loss vs. Hinge Loss Comparison [00:33:12] Concept Check: SVM Practice Questions [00:39:37] Introduction to Decision Trees and Uncertainty [00:42:39] Mathematical Definition of Entropy [00:47:55] Information Gain and Feature Selection [00:58:24] Constructing a Decision Tree: Root Node Selection [01:09:54] Gini Index and Gini Impurity [01:21:51] Handling Continuous Features (Cut Points) [01:25:53] Tree Depth and Overfitting Risks [01:42:25] Resampling Overview: Training, Validation, and Test Sets [01:47:13] Hyperparameter Tuning with Validation Data [01:57:21] Leave-One-Out Cross-Validation (LOOCV) [02:02:29] K-Fold Cross-Validation: Rationale and Implementation [02:07:11] Practice Problem 1: Solving for 3-Fold CV with Ridge Regression candidates. [02:09:45] Technicality: Determining the number of rows in Training Matrix $X$ per fold. [02:11:35] Practice Problem 2: Calculating total model iterations (LOOCV vs. 10-Fold CV). [02:14:02] Concept Review: Why we discard intermediate models and retrain on full data. [02:16:30] Practice Problem 3: MCQ on selecting the final model and estimating generalization error. [02:21:40] Deep Dive: Nested Cross-Validation for Hyperparameter tuning. [02:24:15] Step-by-Step Calculation: How 10 outer folds and 5 inner folds result in 261 iterations. [02:27:50] Practice Problem 4: Identifying the equivalence of LOOCV and M-Fold CV. [02:30:15] Practice Problem 5: Calculating Training Set Error for Linear SVM. [02:33:45] Visual Analysis: Calculating LOOCV Error for SVM decision boundaries. [02:38:20] Case Study: Decision Tree Splitting on real-valued attributes. [02:42:15] Comparison: Training Set Error vs. LOOCV Error for DT2 algorithms. [02:45:30] Final Summary of Resampling Methods for GATE DA. [02:47:11] Why Accuracy is Insufficient for Imbalanced Data [02:51:28] Confusion Matrix: TP, TN, FP, and FN [02:52:57] Precision and Recall Formulas [02:57:40] Use Case Analysis (Surveillance vs. Content Filtering) [03:07:11] ROC Curve and Area Under Curve (AUC) [03:15:51] Analyzing ROC Curve Behavior [03:37:57] R-Squared (R2): Explained Variability [03:44:12] Adjusted R-Squared: Penalty for Irrelevant Features #GATEDA #MachineLearning #LinearRegression #TAAI #ConceptToCombat GATE DA 2026 GATE Data Science AI GATE 2026 preparation GATE DA free course GATE DA practice questions GATE DA MCQ MSQ NAT GATE DA strategy GATE DA toppers preparation GATE DA machine learning Linear algebra for GATE DA Probability for GATE DA GATE DA exam tips GATE DA concepts and questions GATE DA next level preparation TAAI GATE Tomorrow's Architect of AI GATE DA rank oriented GATE DA 2026 full syllabus GATE DA beyond concepts To check out the course- https://www.taai.live/ Join our complete course to boost your GATE DA preparation. 🔹About the complete course: ✅ Complete syllabus coverage for GATE DA. ✅ Concept-focused lectures + regular doubt sessions. ✅ Subject-specific doubt channels. ✅ Expert guidance from our faculty (Manoj Sir, AIR-13 and Sahitya Sir). This course is for anyone who wishes to crack GATE DA, whether you're an absolute beginner or a pro. Join our community: 📌 Website: https://www.taai.live 📌 Telegram: https://t.me/Manoj_Gate_DSAI 📌 Discord:   / discord   📌LinkedIn: https://www.linkedin.com/company/taai... 🔔 Subscribe to our channel and hit the bell icon to get more updates.