Recent questions tagged machine-learning

Given 3 data points in 2-d space, $(1,1),(2,2)$ and $(3,3)$,$(A)$ What is the first principle component ?$(B)$ If we want to project the original data points into 1-d spa...

Let's do principal components analysis (PCA)! Consider this sample of six points $X_i \in \mathbb{R}^2$.$$\left\{\left[\begin{array}{l}0 \\0\end{array}\right],\left[\begi...

$\text { Suppose you were to use PCA on the following dataset }$(a) On the figure above, draw the line that is in the direction of the first principal component of the da...

We now wish to display the first two principal components in a scatterplot. Which of the following plots could potentially display the first two principal components ?ABC...

Suppose we are given three datasets $A, B$, and $C \in \mathbb{R}^{100 \times 2}$ i.e. each dataset consists of 100 data points in two dimensions. We visualize the datase...

Consider two datasets $D^{(1)}$ and $D^{(2)}$ where $D^{(1)} = \{(x_1^{(1)}, y_1^{(1)} ), ..., (x_n^{(1)}, y_n^{(1)}) \}$ and $D^{(2)} = \{x_1^{(2)}, y_1^{(2)} ),...., x...

If the training set is finite and linearly separable, then the perceptron convergence theorem says that the perceptron algorithm will learn a correct linear separator in ...

We ran the perceptron algorithm, with offset, on the following dataset and recorded the number of mistakes we made for each point. Without running the algorithm, what is ...

Which of the following is/are true about the Perceptron classifier?It can learn a OR functionIt can learn a XOR functionThe obtained separating hyperplane depends on the ...

With a linear threshold unit perceptron, implement the NAND function. That is, you should write down the weights $w_0, w_A, w_B$.ABNAND001011101110 

Perceptron. Consider the following Boolean function: $x_1$$x_2$$y = \neg x_1 \bigcup x_2$001011100111Can this function be represented by a perceptron?(Please enter 1 for ...