Linear

In our earlier article, we provided an summary of the sub-categories of supervised learning. Now, we are going to deal with a selected kind of supervised learning called regression evaluation, specifically linear regression.Although regression...

. So if we now have two transformations represented by the matrices A1 and A2 we will apply them consecutively A2(A1(vector)).But that is different from applying them inversely i.e. A1(A2(vector)). That's the reasonIn this...

4 other ways to have a look at itMatrix AB is a sum of p rank-1 matrices of size mxn, where the i_th matrix (amongst p) is the results of multiplying column-i of A...

An Interactive Visualisation for You to Experiment WithSo given the LDA boundary, we will make classifications. But how can we draw the boundary line using the LDA algorithm?The road divides the plot where the...

We also can apply multiple consecutive transformations to a vector. So if we've two transformations represented by the matrices A1 and A2 we will apply them consecutively A2(A1(vector)).But that is different from applying them...

Let’s understand the issue statement before diving into the actual conceptEach regression problem is given X and Y values, and after training with a specific algorithm, it predicts the Y(i) based on the X(i)....

Exploring multi-quantile regression with CatboostThis distribution is correct skewed and has a much higher variance. This is anticipated for this region of information since the noise was sampled from an exponential distribution with high...