In a case where a company wants to detect abnormal patterns in vast amounts of transaction data, which type of neural network model would be particularly beneficial in identifying these anomalies based on data reconstructions?
- Variational Autoencoder
- Long Short-Term Memory (LSTM)
- Feedforward Neural Network
- Restricted Boltzmann Machine
Variational Autoencoders (VAEs) are excellent for anomaly detection because they model data distributions and can recognize deviations from these distributions.
Loading...
Related Quiz
- Which tool or technique is often used to make complex machine learning models more understandable for humans?
- Which process involves transforming and creating new variables to improve a machine learning model's predictive performance?
- You're analyzing data from a shopping mall's customer behavior and notice that there are overlapping clusters representing different shopping patterns. To model this scenario, which algorithm would be most suitable?
- A utility company wants to predict the demand for electricity for the next week based on historical data. They have data for the past ten years, recorded every hour. Which type of machine learning task is this, and what challenges might they face due to the nature of the data?
- In the context of regularization, what is the primary difference between L1 and L2 regularization?