enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Statistical arbitrage - Wikipedia

    en.wikipedia.org/wiki/Statistical_arbitrage

    In finance, statistical arbitrage (often abbreviated as Stat Arb or StatArb) is a class of short-term financial trading strategies that employ mean reversion models involving broadly diversified portfolios of securities (hundreds to thousands) held for short periods of time (generally seconds to days). These strategies are supported by ...

  3. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.

  4. Regularization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Regularization_(mathematics)

    This includes, for example, early stopping, using a robust loss function, and discarding outliers. Implicit regularization is essentially ubiquitous in modern machine learning approaches, including stochastic gradient descent for training deep neural networks, and ensemble methods (such as random forests and gradient boosted trees).

  5. Data augmentation - Wikipedia

    en.wikipedia.org/wiki/Data_augmentation

    Data augmentation is a statistical technique which allows maximum likelihood estimation from incomplete data. [1] [2] Data augmentation has important applications in Bayesian analysis, [3] and the technique is widely used in machine learning to reduce overfitting when training machine learning models, [4] achieved by training models on several slightly-modified copies of existing data.

  6. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics statistical techniques include data modeling, machine learning, AI, deep learning algorithms and data mining. Often the unknown event of interest is in the future, but predictive analytics can be applied to any type of unknown whether it be in the past, present or future.

  7. 5 In-Demand AI Jobs That Pay More Than $100,000 — That You ...

    www.aol.com/finance/5-demand-ai-jobs-pay...

    Key skills and experience needed: Applied mathematics, machine learning, deep learning, ... programming and statistical tools. Data is sourced from FlexJobs and is accurate as of June 24, 2024.

  8. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    Within statistics, oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set (i.e. the ratio between the different classes/categories represented). These terms are used both in statistical sampling, survey design methodology and in machine learning.

  9. Dilution (neural networks) - Wikipedia

    en.wikipedia.org/wiki/Dilution_(neural_networks)

    On the left is a fully connected neural network with two hidden layers. On the right is the same network after applying dropout. Dilution and dropout (also called DropConnect [1]) are regularization techniques for reducing overfitting in artificial neural networks by preventing complex co-adaptations on training data.