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  2. Feature selection - Wikipedia

    en.wikipedia.org/wiki/Feature_selection

    Embedded methods are a catch-all group of techniques which perform feature selection as part of the model construction process. The exemplar of this approach is the LASSO method for constructing a linear model, which penalizes the regression coefficients with an L1 penalty, shrinking many of them to zero.

  3. Relief (feature selection) - Wikipedia

    en.wikipedia.org/wiki/Relief_(feature_selection)

    Relief is an algorithm developed by Kira and Rendell in 1992 that takes a filter-method approach to feature selection that is notably sensitive to feature interactions. [1] [2] It was originally designed for application to binary classification problems with discrete or numerical features.

  4. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    Feature engineering in machine learning and statistical modeling involves selecting, creating, transforming, and extracting data features. Key components include feature creation from existing data, transforming and imputing missing or invalid features, reducing data dimensionality through methods like Principal Components Analysis (PCA), Independent Component Analysis (ICA), and Linear ...

  5. Dimensionality reduction - Wikipedia

    en.wikipedia.org/wiki/Dimensionality_reduction

    The process of feature selection aims to find a suitable subset of the input variables (features, or attributes) for the task at hand.The three strategies are: the filter strategy (e.g., information gain), the wrapper strategy (e.g., accuracy-guided search), and the embedded strategy (features are added or removed while building the model based on prediction errors).

  6. Feature (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Feature_(machine_learning)

    In pattern recognition and machine learning, a feature vector is an n-dimensional vector of numerical features that represent some object. Many algorithms in machine learning require a numerical representation of objects, since such representations facilitate processing and statistical analysis.

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  8. Cross-validation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Cross-validation_(statistics)

    The advantage of this method (over k-fold cross validation) is that the proportion of the training/validation split is not dependent on the number of iterations (i.e., the number of partitions). The disadvantage of this method is that some observations may never be selected in the validation subsample, whereas others may be selected more than once.

  9. Video of military police officer throwing man off bridge ...

    www.aol.com/video-military-police-officer...

    A military police officer has been arrested in Brazil after a video emerged of him throwing a civilian over a bridge in Sao Paulo on Monday, sparking protests in the city.