Multinomial distribution - Learn Data Science with Travis

The Multinomial Probability Distribution

Analytics Vidhya

A multinomial distribution is the probability distribution of the outcomes from a multinomial experiment. A multinomial experiment is a statistical experiment that has the following properties: The…

Multinomial Distribution in R

R-bloggers

Introduction The multinomial distribution is a probability distribution that describes the probability of obtaining a specific number of counts for k different outcomes, when each outcome has a fixed ...

Understanding Multinomial Distribution using Python

Towards Data Science

The multinomial distribution is a generalization of the binomial distribution and is used to find the probabilities in experiments with more than two outcomes. This article gives an intuitive…

The Multinomial Distribution in R

R-bloggers

The post The Multinomial Distribution in R appeared first on Data Science Tutorials What do you have to lose?. Check out Data Science tutorials here Data Science Tutorials. The Multinomial Distributio...

Multinomial Naive Bayes Classifier

Towards Data Science

What we’ll see: What is the multinomial distribution: As opposed to Gaussian Naive Bayes classifiers that rely on assumed Gaussian distribution, multinomial naive Bayes classifiers rely on multinomial...

Multinomial Models for Nominal Data

Towards Data Science

The popular multinomial logistic regression is known as an extension of the binomial logistic regression model, in order to deal with more than two possible discrete outcomes. However, the…

torch.multinomial

PyTorch documentation

Returns a tensor where each row contains num_samples indices sampled from the multinomial probability distribution located in the corresponding row of tensor input . Note The rows of input do not need...

Dice, Polls & Dirichlet Multinomials

Towards Data Science

This article explores a few applications of Bayesian Statistics and the Dirichlet Multinomial distribution using probabilistic programming and PyMC3.

Multinomial Naїve Bayes’ For Documents Classification and Natural Language Processing (NLP)

Towards Data Science

Photo by Arthur V. Ratz Multinomial naïve Bayes’ implementation in Python 3.8, NumPy and NLTK Introduction Naïve Bayes — a probabilistic approach for constructing the data classification models. It’s ...

Support Vector Machines — multinomial example

Towards Data Science

The Iris flower data set is a multivariate data set introduced by the British statistician and biologist Ronald Fisher in his 1936 paper The use of multiple measurements in taxonomic problems. It is…

Presenting results for multinomial logistic regression: a marginal approach using propensity scores

R-bloggers

Multinomial logistic regression modeling can provide an understanding of the factors influencing an unordered, categorical outcome. For example, if we are interested in identifying individual-level ch...

Plot randomly generated multilabel dataset

Scikit-learn Examples

Plot randomly generated multilabel dataset This illustrates the make_multilabel_classification dataset generator. Each sample consists of counts of two features (up to 50 in total), which are differen...