The optimal road trip across the U.S. according to machine learning
rhiever.github.io
The optimal road trip across the U.S. according to machine learning
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Re: The optimal road trip across the U.S. according to machine learning
#2If you're wondering why the route has some 'strange' segments (why get off I-10 to head down Orlando way if you're going to drive to Jacksonville later?):
The link goes to the "Major U.S. landmarks" road trip.
Other trips (including across Canada, South America, and Europe) are listed here: http://rhiever.github.io/optimal-roadtrip-usa/
Re: The optimal road trip across the U.S. according to machine learning
#3If you're wondering why the route has some 'strange' segments (why get off I-10 to head down Orlando way if you're going to drive to Jacksonville later?): The link goes to the "Major U.S. landmarks" road trip. Other trips (including across Canada, South America, and Europe) are listed here: http://rhiever.github.io/optimal-roadtrip-usa/
When it came out a few weeks back, I noticed that it went to the South Rim of the Grand Canyon, which is the popular one. Going to the North Rim would save over 100 miles of driving. To be sure, the South Rim has the better view.
It also can't be done in winter, as its route through Yellowstone isn't open then.
Re: The optimal road trip across the U.S. according to machine learning
#4What does "machine learning" mean here? How does the algorithm guarantee the trip is optimal?
Re: The optimal road trip across the U.S. according to machine learning
#5This is clearly not the optimal road trip, since it passes through Nebraska.
Re: The optimal road trip across the U.S. according to machine learning
#6This is clearly not the optimal road trip, since it passes through Nebraska.
Also Indiana, for its eateries may now legally refuse to serve customers that use machine learning for religous reasons.
Re: The optimal road trip across the U.S. according to machine learning
#7What does "machine learning" mean here? How does the algorithm guarantee the trip is optimal?
And optimal according to what criteria? Length, safety, sightseeing?
Re: The optimal road trip across the U.S. according to machine learning
#8Very curious about the decision metric for "major landmark" here. The San Benito County mark, for example, leads you to a dirt road in the middle of nowhere, and the major point for Delaware is just Delaware. Neither of those seem to fit a reasonable metric for a major landmark.
Re: The optimal road trip across the U.S. according to machine learning
#9Very curious about the decision metric for "major landmark" here. The San Benito County mark, for example, leads you to a dirt road in the middle of nowhere, and the major point for Delaware is just Delaware. Neither of those seem to fit a reasonable metric for a major landmark.
So, I get what you're saying, but the particular locations are completely irrelevant to the math/CS.
Re: The optimal road trip across the U.S. according to machine learning
#10What does "machine learning" mean here? How does the algorithm guarantee the trip is optimal?
In general, "machine learning" means that an algorithm did it, and that the algorithm engages in some analysis of the problem space or the solution space. Usually that analysis involves an iterative or repetitive element: making several tries and modeling what makes a try good or bad, making a try and then changing the solution tiny bits to find a try that's slightly better, etc. And "good" or "bad" is determined according to a human-provided rubric (eg: +1000 points for every sight seen, -1 point for every mile driven, -10 points for every day taken, etc.)
Unless the problem is very constrained, there usually is no guarantee of optimality; here there is probably no guarantee of optimality. It might be "locally" optimal, in that there might be no better trip that differs from this one by only a tiny bit.
And, no, "machine learning" here doesn't mean the enterprise and establishment of "Machine Learning", just some algorithm that the author used.