Generative VS Discriminative Models

Generative VS Discriminative Models

Generative Models- He can learn everything in depth. Generative Model, A Generative Model ‌explicitly models the actual distribution of each class. A Generative Model ‌learns the joint probability distribution p(x,y). It predicts conditional probability with the help of the Bayes Theorem. A joint probability is the likelihood of more than one event occurring at the same time

Generative classifiers

• ‌Naïve Bayes
• Bayesian networks
• Markov random fields
• ‌Hidden Markov Models (HMM)

The Naive Bayes (NB) classifier is a generative model, which builds a model of each possible class based on the training examples for each class. Then, in prediction, given an observation, it computes the predictions for all classes and returns the class most likely to have generated the observation.

HMM

• The Hidden Markov Model (HMM) is a relatively simple way to model sequential data
• A HMM consists of two components. Each HMM contains a series of discrete-state, time-homologous, first-order Markov chains (MC) with suitable transition probabilities between states and an initial distribution
• Model the probabilities of different states and the rates of transitions among them
• HMMs take a generative approach to labeling, defining
• constrained to binary transition and emission feature functions, which force each word to depend only on the current label and each label to depend only on the previous label)
• Markov Assumption: - the probability of a particular state is dependent only on the previous state

Discriminative model

Discriminative mode - Learn the differences between what he saw. Discriminative Model. A Discriminative model ‌models the decision boundary between the classes. A Discriminative model ‌learns the conditional probability distribution p(y|x).

Discriminative Classifiers

• ‌Logistic regression
• Scalar Vector Machine
• ‌Traditional neural networks
• ‌Nearest neighbour
• Conditional Random Fields (CRF)s

In contrast discriminative models, like logistic regression, tries to learn which features from the training examples are most useful to discriminate between the different possible classes

Ref  - Link

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