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Linear Regression, Machine learning term
- 1. S.Rulez Study 1 MachineLearning / Linear Regression
- 2. Machine Learning • Limitationsof explicit programming • Spam filter: many rules • Automatic driving: too many rules • Machine learning "Field of study that gives computers the ability to learn without being explicitly programmed” Arthur Samuel (1959)
- 3. Supervised/Unsupervised learning • Supervisedlearning • Teach the computer how to do something, then let it use it;s new found knowledge to do it • Unsupervised learning • Let the computer learn how to do something, and use this to determine structure and patterns in data
- 4. Supervised learning • Giventhe “right answer” for each example in the data. • learning with labeled examples - training set
- 5. Unsupervised learning • Inunsupervised learning, we get unlabeled data • Just told - here is a data set, can you structure it • To cluster data into to groups - clustering algorithm • Example of clustering algorithm • Google news • Genomics • Organize computer clusters • Social network analysis - Customer data
- 6. Types of supervisedlearning • Predicting final exam score based on time spent • regression • Pass/non-pass based on time spent • binary classification • Letter grade (A, B, C, E and F) based on time spent • multi-label classification
- 7. Regression • a statisticalprocess for estimating the relationships among variables. • 관찰된 연속형 변수들에 대해 두 변수 사이의 모형을 구한 뒤 적합도를 측 정해 내는 분석 방법
- 8. Linear Regression • 종속변수 y와 한 개 이상의 독립 변수 X와의 선형 상관 관계를 모델링 • 독립 변수는 입력값이나 원인, 종속 변수는 결과물이나 효과를 뜻함
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- 11. Hypothesis • It islike your prediction machine, throw in an x value, get a putative y value
- 12. Cost function • Howfit the line to our (training) data • 기대치와 실제 값의 차이를 구하면 되나, 계산의 편의를 위해 차이의 제곱을 구함 • 각 값의 차이의 제곱의 합을 나누어 평균을 구한다.
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- 15. What cost(W) lookslike?
- 16. How to minimizecost?
- 17. Gradient descent algorithm •Minimize cost function • Gradient descent is used many minimization problems • For a given cost function, cost (W, b), it will find W, b to minimize cost • It can be applied to more general function: cost (w1, w2, …)
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- 19. Formal definition Gradient descentalgorithm