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2. Multiclass classification - Wikipedia

   en.wikipedia.org/wiki/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 ). While many classification algorithms (notably multinomial logistic regression ...

3. Decision tree learning - Wikipedia

   en.wikipedia.org/wiki/Decision_tree_learning

   v. t. e. Decision tree learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision tree is used as a predictive model to draw conclusions about a set of observations. Tree models where the target variable can take a discrete set of values are called ...

4. k-nearest neighbors algorithm - Wikipedia

   en.wikipedia.org/wiki/K-nearest_neighbors_algorithm

   k. -nearest neighbors algorithm. In statistics, the k-nearest neighbors algorithm ( k-NN) is a non-parametric supervised learning method first developed by Evelyn Fix and Joseph Hodges in 1951, [1] and later expanded by Thomas Cover. [2] It is used for classification and regression. In both cases, the input consists of the k closest training ...

5. C4.5 algorithm - Wikipedia

   en.wikipedia.org/wiki/C4.5_algorithm

   C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan. [1] C4.5 is an extension of Quinlan's earlier ID3 algorithm. The decision trees generated by C4.5 can be used for classification, and for this reason, C4.5 is often referred to as a statistical classifier. In 2011, authors of the Weka machine learning software ...

6. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Recently, artificial neural networks have been able to surpass many previous approaches in performance.

7. Binary classification - Wikipedia

   en.wikipedia.org/wiki/Binary_classification

   Statistical classification is a problem studied in machine learning. It is a type of supervised learning, a method of machine learning where the categories are predefined, and is used to categorize new probabilistic observations into said categories. When there are only two categories the problem is known as statistical binary classification.

8. Feature (machine learning) - Wikipedia

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

   In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a phenomenon. [1] Choosing informative, discriminating and independent features is a crucial element of effective algorithms in pattern recognition, classification and regression. Features are usually numeric, but structural features ...

9. k-means clustering - Wikipedia

   en.wikipedia.org/wiki/K-means_clustering

   v. t. e. k-means clustering is a method of vector quantization, originally from signal processing, that aims to partition n observations into k clusters in which each observation belongs to the Cluster with the nearest mean (cluster centers or cluster centroid ), serving as a prototype of the cluster. This results in a partitioning of the data ...