ML Project : Weather prediction using Python ( Naïve Bayes ) consist all the commands of Pandas. classification:- Naive Bayes 1.Multinomial 2.Gaussian 3.Bernoulli's
Machine learning project: Weather predicition and Bayes Theorem BAYES THEOREM: is one of the important to make hypothisis about something occures. it simple work like that something event is occured once than it will found out other events.... it is simply constent about conditional probability probability of event a is determined by event b that is popular methology.
Bayes Formula
P(A/B)=P(B/A).P(A)/P(B)
P(A)=probability of event A
P(B)=probability of event B
P(A/B)=Event B already occured based on that event B to find out the event A
P(B/A)=Event A already occured based on that event A to find out event B
we use pandas... why we use pandas___ Pandas allows us to analyze big data and make conclusions based on statistical theories...we use it to read CSV files....Creating the new dataframes . here we can ~ import LableEncoder form sklearn.prepocessing labelEncoder function is very import for this project because in machine learning alogrithms are not trained for reading strings..it only consider data as numericals for converting the strings in the meaning full number we use LabelEncoder and ~import GaussianNB form sklearn.naive_bayes