Answer / Shashi Shekhar Sisodiya

The kernel trick is a technique used in Support Vector Machines (SVM) to handle non-linearly separable data. It maps the input data from the original space into a higher dimensional feature space where the data becomes linearly separable. This transformation is done using a positive definite kernel function like polynomial, Gaussian radial basis function, or sigmoid. The kernel trick allows us to solve complex non-linear problems using SVM without having to explicitly find the mapped feature space.

Define a fourier transform?

1 Answers  

---

What are the different methods of Sequential Supervised Learning?

1 Answers  

---

What is the difference between heuristic for rule learning and heuristics for decision

1 Answers  

---

Is naïve bayes a supervised or unsupervised method?

1 Answers  

---

What are the functions of unsupervised learning?

1 Answers  

---

What is naive bayes used for?

1 Answers  

---

What are different types of Compilers and also define how to convert NFA to DFA?

1 Answers   Tavant Technologies, Verifone,

---

Tell us how do classification and regression differ?

1 Answers  

---

What are the various aspects of a machine learning process?

1 Answers  

---

Differentiate between inductive learning and deductive learning?

1 Answers  

---

What is supervised machine learning?

1 Answers  

---

What is pruning in decision trees and how is it done?

1 Answers  

---