Machine Learning

For a classification problem, Principal Component Analysis (PCA) has been used to reduce the dimensionality of a feature space from 100 to 10. Which of the following options is tru...

Consider that you are training a classifier for a 10-class classification problem. Each input is represented as a 512-dimensional vector. There are 1000 samples, out of which first...

In the following table, the Task column lists a few tasks related to machine learning. The Algorithm column lists a few algorithms. Each entry "t" from the Task column is to be mat...

Consider that for a supervised learning task, the objective function being minimized is $f_w(x) = wx$, where $x \in \mathbb{R}$ is the input and $w \in \mathbb{R}$ is the parameter...

Let four points in three-dimensional space be: P1: [2, 3, -1], P2: [3, 1, 1], P3: [5, -2, 3] and P4: [3, 3, 3]. Hierarchical Agglomerative Clustering is used to cluster the above p...

Consider that 20 stories of Author X and 10 stories of Author Y were kept together without mentioning the names of the authors. A classifier was then asked to predict the author (X...

Consider a fully-connected feed-forward multi-layer perceptron. It has 30 neurons in the input layer, followed by two hidden layers and an output layer. The first hidden layer has...