# Questions tagged [normal-equation]

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### Why adding combinations of features would increase performance of linear SVM?

I have a dataset of ~5000 elements represented by vectors composed by ~30 binary values (0 or 1) on which I am performing binary classification with SVM with linear kernel (I use the Scikit learn lib)...
303 views

### What is the differences between normal equation and gradient descent for polynomial regression

I'm new to machine learning and willing to study and work with machine learning. It just that I still don't get to understand the benefits of using the normal equation in some occasion in comparison ...
231 views

### How does "linear algebraic" weight training function work?

This answer shows that linear and polynomial function weights can be trained using this matrix operation: $w = (X^TX)^{-1}X^Ty$ Therefore, algorithms such as gradient descent are not necessary for ...
5k views

### Gradient Descent or Normal Equation?

Suppose you have a dataset with m = 50 examples and n = 15 features for each example. You want to use multivariate linear regression to fit the parameters theta to our data. Should you prefer gradient ...
671 views

### Polynomial regression vs. multilayer perceptron [closed]

Polynomial regression and multilayer perceptrons have different structures and different learning procedures. What are these two algorithms pros and cons? Are there some situations where one should ...
66 views

### Is it usual for Scikit learn's standard scaler to cause non-invertibility?

For example, I am trying to perform linear regression on the following set of data Data examples: $X = [[1, 20], [3, 40], [5, 60]]$ (each row is an example, there are three examples, each with a ...
Currently I'm taking Andrew Ng's course. He gives a following formula to find solution for linear regression analytically: $θ = (X^T * X)^{-1} * X^T * у$ He doesn't explain it so I searched for it and ...