Logistic Regression using R (Simple / Detailed)

Logistic Regression is a classification machine learning algorithm used to classify your output.
In this video, we will see how you can build a logistic regression (2 level) from scratch and then we can evaluate the performance of the same in simple easy steps.
1) Data profile
2) Data partition
3) Data modeling
4) Testing the machine learning model
5) Evaluate the model performance using
a) Receiver Operating Characteristics curve
b) Confusion Matrix

[@krishnaswamyc9034]

Great content on Classification algorithm

[@divyasukumar7324]

The predictions part is cool..thanks for explaining this..

[@dataexplained7305]

You are welcome...

[@sahelmoein4377]

Hi Sir, thank you for your tutorial. I did data imputation on my small size(n=46) dataset and now need to do exact logistic regression by "elrm" package of R studio. fof is my dependent binary variable, age is numeric and predictor, injuries is binary predictor, minutes and mental health are continious predictors, and race is categorical with three groups. But my code fails because it does not recognize one part "n". I searched in online examples, They did not mention what this n(number of binomial trials) is and how they added this column to their datset.
my code:
data.elrm

[@dataexplained7305]

Sorry for delay. Hope you have figured a way. If not, email your query to [e-mail]

[@SriramakavachamTejaswi]

hi sir, can you give me the link of the data set?

[@dataexplained7305]

Hi.. No problem..
stats.idre.ucla.edu/stat/data/binary.csv