Time series forecasting is hardly a new problem in data science and statistics. The term is self-explanatory and has been on business analysts’ agenda for decades now: The very first practices of time series analysis and forecasting trace back to the early 1920s.
The underlying idea of time series forecasting is to look at historical data from the time perspective, define the patterns, and yield short or long-term predictions on how – considering the captured patterns – target…Continue
Added by Olexander Kolisnykov on February 14, 2018 at 1:58am — No Comments
In the past few years, machine learning (ML) has revolutionized the way we do business. A disruptive breakthrough that differentiates machine learning from other approaches to automation is a step away from the rules-based programming. ML algorithms allowed engineers to leverage data without explicitly programming machines to follow specific paths of problem-solving. Instead, machines themselves arrive at the right answers based on the data they have. This capability made business…Continue
Consider a problem where you are working on a machine learning classification problem. You get an accuracy of 98% and you are very happy. But that happiness doesn’t last long when you look at the confusion matrix and realize that majority class is 98% of the total data and all examples are classified as majority class. Welcome to the real world of imbalanced data sets!!…Continue
Added by Rohit Walimbe on April 24, 2017 at 10:00pm — No Comments