enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The datasets are ported on open data portals. They are made available for searching, depositing and accessing through interfaces like Open API. The datasets are ...

  3. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.

  4. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    Independent: Each outcome will not affect the other outcome (for from 1 to 10), which means the variables , …, are independent of each other. Identically distributed : Regardless of whether the coin is fair (with a probability of 1/2 for heads) or biased, as long as the same coin is used for each flip, the probability of getting heads remains ...

  5. Integrated nested Laplace approximations - Wikipedia

    en.wikipedia.org/wiki/Integrated_nested_Laplace...

    Integrated nested Laplace approximations (INLA) is a method for approximate Bayesian inference based on Laplace's method. [1] It is designed for a class of models called latent Gaussian models (LGMs), for which it can be a fast and accurate alternative for Markov chain Monte Carlo methods to compute posterior marginal distributions.

  6. Caltech 101 - Wikipedia

    en.wikipedia.org/wiki/Caltech_101

    Historically, most data sets used in computer vision research have been tailored to the specific needs of the project being worked on. A large problem in comparing computer vision techniques is the fact that most groups use their own data sets. Each set may have different properties that make reported results from different methods harder to ...

  7. Independent component analysis - Wikipedia

    en.wikipedia.org/wiki/Independent_component_analysis

    In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. [ 1 ]

  8. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    The data sets in the Anscombe's quartet are designed to have approximately the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but are graphically very different. This illustrates the pitfalls of relying solely on a fitted model to understand the relationship between variables.

  9. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    Second, in some situations regression analysis can be used to infer causal relationships between the independent and dependent variables. Importantly, regressions by themselves only reveal relationships between a dependent variable and a collection of independent variables in a fixed dataset.