Building a predictive model with R and Rattle

In this video I see exactly how to build a predictive model, test it and then improve upon it with R and Rattle. This way you can take a model based on current data and make it several percentage points better in accuracy quickly and easily. After all we want our predictive models to have the highest accuracy and levels of confidence possible.

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Example I use this video is from the University of California at Irving. The data set is there bike sharing data set which is publicly available to anyone through their website. If you want to see how to load this data set and do a correlation analysis or similar I have some other videos you should go see same channel.

This specific video we will take the initial model from a 71% to a 77% accuracy or level of confidence. The business world that is a huge difference and that could easily mean the difference between a profit and a loss. Just ask any executive about the importance of a six point spread or what would happen if they could realize a 6% tangible gain based on a predictive analysis you are going to do for them.

Predictive analytics is the wave of the future. Building predictive models as fast and accurately as possible through applications like Rattle and R is becoming super important. The best part is this required absolutely no coding or programming.

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