What assumptions are required for linear regression

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Reference no: EM131944411

Problem

1. Suppose we are training a model using stochastic gradient descent. How do we know if we are converging to a solution?

2. Do gradient descent methods always converge to the same point?

3. What assumptions are required for linear regression? What if some of these assumptions are violated?

4. How do we train a logistic regression model? How do we interpret its coefficients?

Reference no: EM131944411

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