Skip to content

The objective is predict the percentage of chance a flight being delayed. If there was a delay in the arrival of the flight, it's considered a delay. Tools: Spark, RDDs, Spark ML

Notifications You must be signed in to change notification settings

jeffersonlbr/flights-prediction

Repository files navigation

Analysis objective

Detect whether a specific flight has the potential to be delayed or not.

The dataset

Challenge of flights

The challenge itself was to detect, through machine learning models, whether a flight is more likely to be canceled or not. My final model was inform the percentage possibility to delay each flight. With this model, airlines can use to make better decisions to take preemptive actions that do not impact passengers. My regression model prediction is fluctuating around 65 points in relation to the actual value. Can be improved adding more data from the previous years also.

About

The objective is predict the percentage of chance a flight being delayed. If there was a delay in the arrival of the flight, it's considered a delay. Tools: Spark, RDDs, Spark ML

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages