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  2. Deadweight loss - Wikipedia

    en.wikipedia.org/wiki/Deadweight_loss

    In modern economic literature, the most common measure of a taxpayer's loss from a distortionary tax, such as a tax on bicycles, is the equivalent variation, the maximum amount that a taxpayer would be willing to forgo in a lump sum to avoid the tax. The deadweight loss can then be interpreted as the difference between the equivalent variation ...

  3. Data envelopment analysis - Wikipedia

    en.wikipedia.org/wiki/Data_envelopment_analysis

    Data envelopment analysis (DEA) is a nonparametric method in operations research and economics for the estimation of production frontiers. [1] DEA has been applied in a large range of fields including international banking, economic sustainability, police department operations, and logistical applications [2] [3] [4] Additionally, DEA has been used to assess the performance of natural language ...

  4. List of datasets for machine-learning research - Wikipedia

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

    Covertype Dataset Data for predicting forest cover type strictly from cartographic variables. Many geographical features given. 581,012 Text Classification 1998 [311] [312] J. Blackard et al. Abscisic Acid Signaling Network Dataset Data for a plant signaling network. Goal is to determine set of rules that governs the network. None. 300 Text

  5. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    This works by partitioning the data set into equal-sized buckets and aggregating the data within each bucket. This pre-aggregated data set becomes the new sample data over which to draw samples with replacement. This method is similar to the Block Bootstrap, but the motivations and definitions of the blocks are very different.

  6. Lift (data mining) - Wikipedia

    en.wikipedia.org/wiki/Lift_(data_mining)

    because these are simply the most common patterns found in the data. A simple review of the above table should make these rules obvious. The support for Rule 1 is 3/7 because that is the number of items in the dataset in which the antecedent is A and the consequent 0. The support for Rule 2 is 2/7 because two of the seven records meet the ...

  7. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  8. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [ 10 ] Data analysis is a process for obtaining raw data , and subsequently converting it into information useful for decision-making by users. [ 1 ]

  9. Oversampling and undersampling in data analysis - Wikipedia

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

    The feature space for the minority class for which we want to oversample could be beak length, wingspan, and weight (all continuous). To then oversample, take a sample from the dataset, and consider its k nearest neighbors (in feature space). To create a synthetic data point, take the vector between one of those k neighbors, and the current ...