Welcome to the last part of the series on predicting user’s revisit to the website. In the first part of series, I generated the logistic regression model for prediction problem whether a user will come back on website in next 24 hours. In the second part, I discussed about model improvement and seen the model accuracy.
Welcome to the second part of the series on predicting user’s revisit to the website. In my earlier blog Logistic Regression with R, I discussed what is logistic regression. In the first part of the series, we applied logistic regression to available data set. The problem statement there was whether a user will return in
In my earlier blog, I have discussed about what is logistic regression? And how logistic model is generated in R? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict whether a user will return on website in next 24 hours. This
Logistic Regression In my first blog post, I have explained about the what is regression? And how linear regression model is generated in R? In this post, I will explain what is logistic regression? And how the logistic regression model is generated in R? Let’s first understand logistic regression. Logistic regression is one of the
Welcome to the second part. In the last blog post on Linear Regression with R, we have discussed about what is regression? and how it is used ? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict bounce rate as function
Regression Through this post I am going to explain How Linear Regression works? Let us start with what is regression and how it works? Regression is widely used for prediction and forecasting in field of machine learning. Focus of regression is on the relationship between dependent and one or more independent variables. The “dependent variable”
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
