💡 Words with a Similar Meaning to "Linear classifier"
Found via reverse dictionary — words that share a conceptual meaning.
| Word | Definition |
|---|---|
| statistical classification | When classification is performed by a computer, statistical methods are normally used to develop the algorithm. |
| probabilistic classification | In machine learning, a probabilistic classifier is a classifier that is able to predict, given an observation of an input, a probability distribution over a set of classes, rather than only outputting the most likely class that the observation should belong to. |
| sequence labeling | In machine learning, sequence labeling is a type of pattern recognition task that involves the algorithmic assignment of a categorical label to each member of a sequence of observed values. |
| multiclass classification | In machine learning and statistical classification, multiclass classification or multinomial classification is the problem of classifying instances into one of three or more classes (classifying instances into one of two classes is called binary classification). |
| feature learning | In machine learning, feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations needed for feature detection or classification from raw data. |
| one-class classification | In machine learning, one-class classification, also known as unary classification or class-modelling, tries to identify objects of a specific class amongst all objects, by primarily learning from a training set containing only the objects of that class, although there exist variants of one-class classifiers where counter-examples are used to further refine the classification boundary. |
| cluster analysisnoun | (artificial intelligence, statistics) The classification of objects into different groups, or more precisely, the partitioning of a data set into subsets (clusters), so that the data in each subset (ideally) share some common trait - often proximity according to some defined distance measure. |
| featurenoun | An important or main item. |
| system identification | alt=System identification methods.png|thumb|System identification methods.png |
| margin classifier | In machine learning, a margin classifier is a type of classification model which is able to give an associated distance from the decision boundary for each data sample. |
| multi-label classification | In machine learning, multi-label classification or multi-output classification is a variant of the classification problem where multiple nonexclusive labels may be assigned to each instance. |
| structured prediction | Structured prediction or structured output learning is an umbrella term for supervised machine learning techniques that involves predicting structured objects, rather than discrete or real values. |
| classificationnoun | The act of forming into a class or classes; a distribution into groups, as classes, orders, families, etc., according to some common relations or attributes. |
| quadratic classifier | In statistics, a quadratic classifier is a statistical classifier that uses a quadratic decision surface to separate measurements of two or more classes of objects or events. |
| hierarchical clustering | In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters. |
| similarity measure | In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. |
| feature selection | In machine learning, feature selection is the process of selecting a subset of relevant features (variables, predictors) for use in model construction. |
| diagnosisnoun | (medicine, countable, uncountable) The process of, or an instance of, identification of the nature and cause of a medical condition or illness. |
| predictive analytics | Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. |
| supervised learning | In machine learning, supervised learning is a paradigm where a model is trained using input objects (e.g. a vector of predictor variables) and desired output values (also known as a supervisory signal), which are often human-made labels. |
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