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AdaBoost
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AdaBoost

ByDavis

AdaBoost is a machine learning algorithm that is used to improve the accuracy of predictions made by a model. It does this by iteratively training a model on a subset of the data, and then using the model to predict the outcomes for the remaining data.

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Outlier

ByDavis

Definition of Outlier Outlier: An outlier is a data point that is significantly different from the other points in the dataset. Outliers can be caused by errors in data collection or by natural variations in the data. They can be removed from a dataset before analysis, or they can be studied to learn more about…

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Feature

ByDavis

Definition of Feature A feature is a characteristic of something, often used to describe data. In machine learning, features are the variables that are used to train and predict models. Good features are important for making accurate predictions, so it is important to select the most relevant features for your data set. What is a…

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Hyperplane

ByDavis

Definition of Hyperplane Hyperplane: A hyperplane is a mathematical concept used in linear algebra and machine learning. It is a subspace of a given vector space that is spanned by a set of vectors. In other words, it is a flat plane in a higher dimensional space. Hyperplanes can be used to separate different classes…

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False Positive

ByDavis

Definition of False Positive False Positive: False positive is a result that incorrectly identifies an event as being positive. What are False Positive used? False Positive is a term used in data science and machine learning that refers to an incorrect classification of an item as being positive when, in reality, it is negative. It…

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