Which two techniques are used to build personas in the ML development lifecycle? (Select two.)
A support-vector machine (SVM) is a supervised learning algorithm that can be used for classification or regression problems. An SVM tries to find an optimal hyperplane that separates the data into different categories or classes. However, sometimes the data is not linearly separable, meaning there is no straight line or plane that can separate them. In such cases, a polynomial kernel can help improve the prediction of the SVM by transforming the data into a higher-dimensional space where it becomes linearly separable. A polynomial kernel is a function that computes the similarity between two data points using a polynomial function of their features.
Truman
8 months agoShantay
8 months agoGlendora
9 months agoLorenza
9 months agoFelicitas
9 months agoLaticia
9 months agoGladys
10 months agoTesha
10 months agoMarisha
10 months agoFelix
10 months agoTegan
10 months agoCassandra
10 months agoYuette
10 months agoRegenia
10 months agoFreeman
10 months agoGoldie
10 months agoIluminada
10 months agoReena
1 year agoMeaghan
1 year agoRikki
1 year agoMy
1 year agoCarma
1 year agoAracelis
1 year agoValentin
1 year agoFrederick
1 year agoBrendan
1 year agoCyndy
1 year agoErasmo
1 year agoHarris
1 year agoAlaine
1 year agoLaila
1 year agoTimothy
1 year agoMonte
1 year agoKristel
1 year agoKanisha
1 year agoSylvie
1 year agoJill
1 year ago