The newly identified planet, Kepler-90i, is a rocky planet like Earth, but orbits its star once every 14.4 days, meaning a full year there is the same as two weeks on Earth.
"Just as we expected, there are exciting discoveries lurking in our archived Kepler data, waiting for the right tool or technology to unearth them", Paul Hertz, director of NASA's Astrophysics Division, said in a statement. "Machine learning really shines in situations where there is so much data that humans can't search it for themselves".
Additionally, an Earth-sized planet was spotted orbiting Kepler-80, the release said.
The Kepler-90 planets have a similar configuration to our Solar System with small planets found orbiting close to their star, and the larger planets found farther away. With help from Andrew Vanderburg, an astronomer at the University of Texas at Austin, Shallue developed a machine-learning program that detects light curves.
"Maybe there are systems out there with so many planets that they make our eight-planet solar system seem ordinary".
After this discovery, the Kepler-90 solar system has come at par with our own in terms of number of planets revolving around a single star, said NASA.
In recent years, to tackle data analysis in science, finance and other industries by automated software is possible due to advancements in hardware and new techniques in machine learning. It can potentially be used to find astronomical bodies that have been missed in previous searches.
Kepler has produced an unprecedented data set for exoplanet hunting.
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"The Kepler mission has so much data, it is impossible to examine manually", Christopher Shallue, a Google AI software engineer, explained during the briefing. However, the weakest signals often are missed using these methods.
Aimed at distant planet researchers, Mr. Vanderburg has received funding through a NASA fellowship.
Like Earth, this new planet, Keplar-90i, is the third rock from its sun. In comparison, Mercury's orbit is 88 days.
All of the planets except for 90i were previously known.
"In my spare time, I started Googling for "finding exoplanets with large data sets" and found out about the Kepler mission and the huge data set available", he said.
"We've come a long way in our understanding of planetary systems", said Jessie Dotson, Kepler's project scientist at NASA's Ames Research Center in Northern California, which manages the Kepler and K2 missions.
The neural network is trained on 15,000 signals from the Kepler dataset that have been previously verified as planets or non-planets.
If you want to search for planets among Kepler's weaker signals - which are far more numerous - then that haystack gets "much, much larger", he added.
When the scientists finally tested their neural network on signals that it had not seen before, it correctly sorted the planets from the false positives a whopping 96% of the time, Shallue said.
According to Space.com, "Kepler spots alien worlds by noticing the tiny brightness dips they cause when they cross the face of their host star from the spacecraft's perspective".
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