Recent questions tagged machine-learning

Suppose you have the following training set with three boolean input $x, y$ and $z$, and a boolean output $U$.\begin{array}{|c|c|c|c|}\hline x & y & z & U \\\hline \hline...

\begin{array}{|c|c|c|}\hline A_1 & A_2 & \text { Class Label } Y \\\hline \text { True } & \text { True } & + \\\hline \text { True } & \text { True } & + \\\hline \text ...

Suppose we are given the following dataset, where $A, B, C$ are input binary random variables, and $y$ is a binary output whose value we want to predict.\begin{array}{|c|...

What is the total number of parameters needed to model $P\left(Y, X_1, X_2, X_3, \cdots, X_d\right) ?$$k$ is the number of possible values $Y$ can take.$t$ is the number ...

Suppose that you are trying to solve a binary classification problem, and your data set has 4 attributes. Each attribute can take 3 possible values.If you modeled the ful...

Consider a naive Bayes classifier with 3 boolean input variables, $X_1, X_2$ and $X_3$, and one boolean output, $Y$.How many parameters must be estimated to train such a ...

You have a green-black avocado, and want to know if it is ripe. Based on this data, would you predict that your avocado is ripe or unripe?\begin{array}{|l|l|}\hline \text...

Imagine you are using a $k$-Nearest Neighbor classifier on a dataset with lots of noise. You want your classifier to be less sensitive to the noise. Which of the followin...

In the image below, which would be the best value for $k$, assuming you are using the $k$-nearest neighbor algorithm ?3102050

For any two neighboring Voronoi cells $C_1$ and $C_2$ corresponding to two training examples $\mathbf{x}^{(1)}$ and $\mathbf{x}^{(2)}$, the boundary between $C_1$ and $C_...

You are using K-Nearest Neighbors (KNN) regression with $K=3$. Below is the dataset of the nearest neighbors and their corresponding target values:\begin{array}{|l|l|l|}\...

Consider a classification problem where the training dataset consists of $n$ data points that all have different feature values. Mark the correct statementsA $k$-nearest-...

Consider a 2D dataset where training points are on the integer grid $\left(x_1, x_2\right)$, and both dimensions $x_1$ and $x_2$ range from 1 to 100 (inclusive). The bina...

What is the training error (fraction labeled wrong) in the above picture using 1 -nearest neighbor and the $L_1$ distance norm between points? If there is more than one e...

Consider a set of five training examples given as $\left(\left(x_i, y_i\right), c_i\right)$ values, where $x_i$ and $y_i$ are the two attribute values (positive integers)...

$\text { What would be the class assigned to this test instance for } \mathrm{K}=1, \mathrm{K}=3 \quad and \quad \mathrm{K}=5 $ $\text{respectively.}$$+,-,+$$-,-,+$$-,-,...

Logistic regression is named after the log-odds of success (the logit of the probability) defined as$$\ln \left(\frac{\mathbb{P}[Y=1 \mid X=x]}{\mathbb{P}[Y=0 \mid X=x]}\...

$\text { What is the range of possible values for log odds in probability ? }$0 to 1-1 to 10 to $\infty$$-\infty$ to $\infty$

$\text{What is the range of possible values for odds in probability ?}$ 0 to 10 to $\infty$-1 to 1$-\infty$ to $\infty$

Give the possible feature transformation such that given data is linearly separable. 

Give the possible feature transformation such that given data is linearly separable. 

Consider the following image data point, where the model's predicted probabilities for the classes (Dog, Cat, Mountain) are:\begin{array}{ll}\text { Class } & \text { Pro...

Consider the function $f: \mathbb{R}^d \mapsto \mathbb{R}^d$ whose components are given by$$f_i(x)=\frac{x_i^2}{\sum_{k=1}^d x_k^2}$$for $i=1, \ldots, d$ and $x \in \math...