Arthur Samuel(1959) : Machine Learning is field of study that gives computers the ability to learn without being explicitly programmed머신 러닝은 컴퓨터가 프로그램
The most common method for fitting a regression line is the method of least-squares.
기존의 Original Linear regression algorithm과 Locally weighted linear regression algorithm은 다음과 같은 차이가 있다.Here the w(i) are non-negative valued weights.If
1. Generalized Linear Models
1. Generative Learning Algorithms Consider a classification problem in which we want to learn to distinguish between elemphants(y=1) and dogs(y=0), b
Support Vector Machine은 Decision Boundary, 즉 분류를 위한 기준선을 정의하는 모델이다. 분류되지 않은 새로운 점이 나타날 때 경계의 어느 쪽에 속하는지 확인하여 분류 과제를 수행하게 함이 목적이다.Margin은 결정 경계와 서포트 벡터
In Linear regression, we had a problem in which the input x was the living area of a house and we considered performing regression using the features
1. Bias/Variance The generalization error of a hypothesis is its expected error on examples not necessarily in the training set. Informally we defin