# Questions tagged [normal-equation]

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### Loss-value of normal equation vs gradient descent

My question is if gradient descent can give a better aproximation than normal equation in Python? for the Loss function, I wrote ...
• 103
1 vote
290 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 ...
• 123
96 views

### Normal equation for linear regression is illogical

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 ...
• 123
1 vote
8k 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 ...
365 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 ...
• 23
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### Linear Regression - finding thetha using Normal equation

This is to find thetha which will give minimum cost function. Why is the x0 column required? why cant we assign size as x0? why do we need the feature count to be n+1?
• 149
1 vote
350 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 ...
• 409
1k views

### 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)...
• 33
1 vote