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In probability theory and statistics, the Bernoulli distribution, named after Swiss mathematician Jacob Bernoulli, is the discrete probability distribution of a random variable which takes the value 1 with probability and the value 0 with probability, in this example we will be able to visualize that in graphics mode
Data distribution is a function that lists out all possible values the Data can take. It can be a continuous or discrete Data distribution. Several known standard Probability Distribution functions provide probabilities of occurrence of different possible outcomes in an experiment.
Used data of emails being spam or non-spam for performing text classification using different probability distributions. Used NLTK library to remove stop words, non-alphabetic characters, and for tokenizing the text. Calculated mean and variance and other params for each word based on the label(spam or ham).
Write a program (in your favorite language) to obtain N samples from each of the following distributions: (i) Bernoulli with μ = 0.5; (ii) Poisson with parameter λ = 5; and (iii) Uniform on [0, 10].
Using the Bernoulli distribution this terminal app works by passing arguments for the total instance count, positive instances out of those total ones, positive variants, total variants.
Used data of emails being spam or non-spam for performing text classification using different probability distributions. Used NLTK library to remove stop words, non-alphabetic characters, and for tokenizing the text. Calculated mean and variance and other params for each word based on the label(spam or ham).
This repository has been created to complete an assignment given by datainsightonline.com. This assignment is a part of Data Insight | Data Science Program 2021.