Model Assessment: Metrics and Selection

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (54)

Evaluation Protocols Log in to Mediaspace to watch this video

Explores evaluation protocols in machine learning, including recall, precision, accuracy, and specificity, with real-world examples like COVID-19 testing.

Untitled Log in to Mediaspace to watch this video

Estimating Relaxation Time: Variance and Chains Log in to Mediaspace to watch this video

Covers the estimation of relaxation time in chains and the importance of sample sizes.

Classification pipeline: building and evaluating Log in to Mediaspace to watch this video

Explains building and evaluating a classification pipeline using tweet data sets.

Receiver-Operator Characteristics: ROC Curves Log in to Mediaspace to watch this video

Explains ROC curves, Precision-Recall curve, RMSLE, and model validation.

Error Estimation in LHS Log in to Mediaspace to watch this video

Covers error estimation in Latin Hypercube Sampling, emphasizing the importance of accurate variance estimation.

Sampling: Signal Reconstruction and Aliasing Log in to Mediaspace to watch this video

Covers the importance of sampling, signal reconstruction, and aliasing in digital representation.

Structures and Mechanisms: Opening a Box Log in to Mediaspace to watch this video

Explores the analysis of structures and mechanisms through a sample problem of opening a box with a string-held lid.

Review Session: Module 1 Log in to Mediaspace to watch this video

Introduces inferential statistics, covering sampling, central tendency, dispersion, histograms, z-scores, and the normal distribution.

Signals & Systems I: Sampling and Reconstruction Log in to Mediaspace to watch this video

Explores ideal sampling, Fourier transformation, spectral repetition, and analog signal reconstruction.

Stochastic Simulation: Metropolis-Hastings Algorithm Log in to Mediaspace to watch this video

Covers the Metropolis-Hastings algorithm and convergence diagnostics in stochastic simulation, focusing on sampling and proposal generation.

Principal Component Analysis: Dimension Reduction Log in to Mediaspace to watch this video

Explores Principal Component Analysis for dimension reduction in datasets and its implications for supervised learning algorithms.

Untitled Log in to Mediaspace to watch this video

Important Sampling: Monte Carlo Estimation Log in to Mediaspace to watch this video

Covers important sampling for efficient Monte Carlo estimation of expected values using a new distribution to reduce variance.

Page 3 of 3