A classification or categorical variable expresses the membership of a data item in one or more discrete groups. The number of classifications predicted by a model is necessarily finite. Classifications are often contrasted with quantitative variables. More explanation can be found here.
- used by
- ALG_Actor-critic ALG_Adaptive resonance theory network ALG_Averaged one-dependence estimators ALG_Bayesian network ALG_Convolutional neural network ALG_Decision tree ALG_Deep Q-network ALG_Discriminant analysis ALG_Expectation maximization ALG_Hierarchical clustering ALG_Logistic regression ALG_Long short-term memory network ALG_Markov random field ALG_Monte-Carlo tree search ALG_Naive Bayesian Classifier ALG_Nearest Neighbour ALG_Neural actor-critic ALG_One Rule ALG_Perceptron ALG_Policy gradient estimation ALG_Probabilistic latent semantic indexing ALG_Q-learning ALG_Radial basis function network ALG_Random forest ALG_SARSA ALG_Spherical k-means ALG_Support vector machine ALG_Temporal difference learning ALG_Zero Rule ALG_k-means ALG_k-medians ALG_k-medoids