반응형 Computer Science/기계학습25 [Classification 2] 3. Classification algorithms - SVM( SUPPORT VECTOR MACHINE ): Non-linear SVM – Kernel trick Content Introduction to supervised learning approach Data split in supervised learning Classification algorithms KNN & distance measures Decision tree Random Forest, Ensemble approach SVM 3. Classification algorithms - SVM( SUPPORT VECTOR MACHINE ) SVM: Content 1. Linear SVM 2. Linear SVM: non-separable case 3. Non-linear SVM – Kernel trick 3.18 Non-linear SVMs 선형으로 분리 가능한 데이터셋에 약간의 잡음이 있을 때, 선형.. 2024. 4. 22. [Classification 2] 3. Classification algorithms - SVM( SUPPORT VECTOR MACHINE ): Linear SVM ContentIntroduction to supervised learning approachData split in supervised learningClassification algorithmsKNN & distance measuresDecision treeRandom Forest, Ensemble approachSVM3. Classification algorithms - SVM( SUPPORT VECTOR MACHINE ) SVM: Content 1. Linear SVM 2. Linear SVM: non-separable case 3. Non-linear SVM – Kernel trick3.1 SVM: IntroductionSVM, 즉 Support Vector M.. 2024. 4. 22. [Classification 2] 3. Classification algorithms - Random Forest, Ensemble approach(2) Content Introduction to supervised learning approach Data split in supervised learning Classification algorithms KNN & distance measures Decision tree Random Forest, Ensemble approach SVM 3. Classification algorithms - Random Forest, Ensemble approach 3.17 Random Forest with different values of “m” Random Forest 알고리즘에서 다양한 "m" 값의 사용은 중요한 의미를 가집니다. 여기서 "m"은 각 결정 트리를 생성할 때 무작위로 선택되는 특성(변수)의 수를 의미합.. 2024. 4. 22. [Classification 2] 3. Classification algorithms - Random Forest, Ensemble approach(1) Content Introduction to supervised learning approach Data split in supervised learning Classification algorithms KNN & distance measures Decision tree Random Forest, Ensemble approach SVM 3. Classification algorithms - Random Forest, Ensemble approach 3.1 Problem with a single best model 이전에 논의된 결정 트리는 높은 변동성(variance)을 가지고 있다는 문제가 있습니다. 만약 우리가 훈련 데이터를 무작위로 2부분으로 나누고, 각 부분에 대해 결정 트리를 적용한다면, 결과는 .. 2024. 4. 21. 이전 1 2 3 4 5 6 7 다음 반응형
