Day #41 - Machine Learning Interesting Qns

I do read through a lot of materials. Some readings are very clear and needs bookmark. Some of those questions and answers

1. How does KNN predict class label for new example ?
• Find the nearest K neighbour of example which needs to be classified. Take the major vote based on class labels of the K neighbours found
2. Classification - Map input to discrete outputs
3. Generative Model - Naive Bayes
4. Discriminative Model - SVM, Decision Trees, Neural Networks, Boosting, KNN
5. Regression - Map input to continuous outputs
6. Decision Tress - Embedded Implicit Feature Selection method
7. PCA
• Taking Data into a new space
• Number of Eigen Values = Number of original dimensions
• Pick the top k Eigen Value Vectors

       8. Linearly non-separable in normal plane. With SVM Kernal Technique we can project it in hyper plane and make it linearly separable

       
       9. Linearly Separable

Happy Learning!!!