Recent questions tagged goclasses-ml-practice-questions

Suppose we build a neural network for a 5-class classification task. Suppose for a single training example, the true label is $\left[\begin{array}{lllll}1 & 0 & 0 & 0 & 0...

Consider a neural network with the number of neurons in different layers as mentioned in the below list for a regression task. The first layer is the input layer and the ...

Consider a neural network with the number of neurons in different layers as mentioned in the below list for a regression task. The first layer is the input layer and the ...

Consider a neural network with the number of neurons in different layers as mentioned in the below list for a regression task. The first layer is the input layer and the ...

Consider the following data:\[\begin{array}{|l|l|}\hlineg(x) & y \\\hline+30 & +1 \\\hline-20 & -1 \\\hline-1 & -1 \\\hline+1 & +1 \\\hline\end{array}\]Which of the follo...

We have trained four models in the same dataset with different hyperparameters. In the following table, we have recorded the training and testing errors for each of the m...

We have trained four models in the same dataset with different hyperparameters. In the following table, we have recorded the training and testing errors for each of the m...

Is the following statement true or false?If $i^{\text {th }}$ point in soft-margin SVM pays a non-zero bribe ( $\xi_i>0$ ), then the value of $\alpha_i$ is $C$.TRUE FALSE...

Is the following statement true or false?If a point lies between the supporting hyperplanes in the soft-margin SVM problem, it always pays a positive bribe and plays a ro...

Background Information:Before choosing an answer, consider the following definition for the SVM approach:Kernel Method: This technique is used when the data is not linear...

Consider the following training dataset for a binary classification problem in $\mathbb{R}^2$. Each data-point is represented by $\mathbf{x}=\left[\begin{array}{ll}x_1 & ...

Consider a linearly separable dataset for a binary classification problem in $\mathbb{R}^d$. Three linear classifiers have been trained on this dataset. All three pass th...

Consider a data set $x_1=\left[\begin{array}{l}-1 \\ -1\end{array}\right], x_2=\left[\begin{array}{c}-1 \\ 0\end{array}\right], x_3=\left[\begin{array}{l}0 \\ 1\end{array...

  Blue line Brown line Both None of these

If the scores (i.e, $w^T x$ values) for some data points are $-4,3,1,2,-6$ respectively, what will be the probabilities returned for these points by Logistic Regression?$...

Given a linearly separable data set where the maximum Euclidean norm of any data point is $R=4$ (i.e., $\max \|x\|=4$), and the margin of separation is $\gamma=2$, what i...

  if the weight vector is multiplied by $-1$ , which classes will be predicted by the Perceptron for the data points $x_1$ and $x_2$ ?$x_1:+1, x_2:-1$ $x_1:-1, x_2:+1$ $x...

 Consider ten data points as shown in the following image:  The blue line represents the weight vector. As per this weight vector, the Perceptron algorithm will predict w...

Consider the following data set with three data points:$$\left(\left[\begin{array}{l}2 \\2\end{array}\right],+1\right),\left(\left[\begin{array}{c}2 \\-2\end{array}\right...

Consider the following data set:\[\begin{array}{|c|c|c|}\hlinef_1 & f_2 & y \\\hline-1 & -1 & -1 \\0 & 1 & +1 \\1 & 0 & +1 \\1 & 1 & +1 \\\hline\end{array}\]If the Percep...

Assume that the Perceptron algorithm is applied to a data set in which the maximum of the lengths of the data points is $4$ and the value of the margin ( $\gamma$ ) of th...

A binary classification dataset has 1000 data points belonging to $\{0,1\}^2$. A naive Bayes algorithm was run on the same dataset that results in the following estimate:...

A binary classification dataset has 1000 data points belonging to $\{0,1\}^2$. A naive Bayes algorithm was run on the same dataset that results in the following estimate:...

Consider the following binary classification dataset with two features $f_1$ and $f_2$. The data points given the labels follow the Gaussian distribution. The dataset is ...

Consider a binary classification dataset containing two features $f_1$ and $f_2$. The feature $f_1$ is categorical which can take three values and the feature $f_2$ is nu...

Consider the following binary classification dataset with two features $f_1$ and $f_2$. The data points given the labels follow the Gaussian distribution. The dataset is ...

Consider a binary classification dataset with two binary features, $f_1$ and $f_2$. The $f_2$ feature values are 0 for all label '$0$' examples but the label '$1$' exampl...

Consider a binary classification dataset contains only one feature and the data points given the label follow the given distribution$$\begin{aligned}& x \mid(y=0) \sim \m...

A naive Bayes model is trained on a dataset containing $d$ features $f_1, f_2, \ldots, f_d$. Labels are 0 and 1. If a test point was predicted to have the label 1 , which...