Bayesian Probability Definitions and Classifiers

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What type of activation functions are used to predict discrete values in classification tasks?

Linear

Sigmoid

Nonlinear (correct)

Step

Which metric is also known as Log Loss?

Area Under Curve (AUC)

Recall

Logarithmic Loss (correct)

Precision

What is the purpose of Area Under Curve (AUC) in binary classification?

Performance measurement (correct)

Measuring accuracy

Evaluating recall

Assessing precision

What does the True Positive Rate measure in classification models?

Positive predictions that are actually correct Signup and view all the answers

In which direction does data move in a Feedforward neural network architecture?

Forward only Signup and view all the answers

What is the trade-off between recall and precision?

Higher recall means lower precision Signup and view all the answers

What is the goal of the Naïve Bayes algorithm?

To create the best line or decision boundaries Signup and view all the answers

What is the main purpose of the Linear SVM classifier?

To classify datasets into two classes using a single straight line Signup and view all the answers

Which algorithm is primarily utilized in text classification?

Naïve Bayes Signup and view all the answers

What does the term 'Support Vectors' refer to in machine learning?

Extreme points/vectors that help in creating the hyperplane Signup and view all the answers

In machine learning, what is Posterior Probability denoted by P(A|B)?

Probability of hypothesis A on the observed event B Signup and view all the answers

What does the Non-linear SVM classifier help to classify?

Non-linearly separated data Signup and view all the answers

What is the primary use of a Bernoulli classifier?

Document classification problems Signup and view all the answers

What does the topmost node in a decision tree represent?

Feature Signup and view all the answers

What type of data distribution is assumed by a Multinomial naïve Bayes classifier?

Multinomial distribution Signup and view all the answers

In artificial neural networks, what is adjusted during backpropagation?

Weights Signup and view all the answers

What problem is Long Short-Term Memory (LSTM) designed to overcome?

Vanishing gradient Signup and view all the answers

Which neural network architecture is commonly used for image processing?

CNN (Convolutional Neural Network) Signup and view all the answers

What is the primary function of hidden layers in neural networks?

Process inputs by multiplying them by weights, adding them up, and passing them through an activation function Signup and view all the answers

Perceptrons are limited to solving which type of issues?

Linearly separable issues Signup and view all the answers

Forward propagation in neural networks involves which process?

Passing data forward through the network to generate an output Signup and view all the answers

Convolutional Neural Networks (CNNs) introduce non-linearity in models through what?

Activation functions like ReLU or sigmoid Signup and view all the answers

'Weights and connections' are central to the functioning of which early concept of artificial neurons?

Perceptrons (1960s - 1970s) Signup and view all the answers

What concept was introduced in the 1990s that consists of a flowchart-like tree structure with nodes representing features?

Decision tree Signup and view all the answers