Popular Machine Learning algorithms(medium.com)
medium.com
Popular Machine Learning algorithms
https://medium.com/technology-nineleaps/popular-machine-learning-algorithms-a574e3835ebb
7 comments
An example of such tool https://github.com/paypal/autosklearn-zeroconf
There are many more including genetic algorithms. Some are discussed here: https://www.reddit.com/r/MachineLearning/comments/6efs8u/d_a...
There are many more including genetic algorithms. Some are discussed here: https://www.reddit.com/r/MachineLearning/comments/6efs8u/d_a...
TPOT is also a good automl package that utilizes sklearn in Python. It's also actively under development. (I'm not affiliated, just an occasional user)
https://github.com/rhiever/tpot
https://github.com/rhiever/tpot
You might also be interested to check out Automatic Statistician (developed by Z. Ghahramani, J. Tenenbaum and others) - https://www.automaticstatistician.com/index/
The keyword you are looking for is AutoML. http://automl.info/
You can state that a neural network is a hypothesis set, but is it useful when you've got a hypothesis that is 100's of values each with billions of possible values? I mean why talk about that in terms of a set?
From their link:
>"Hypothesis set is the set of functions that have some common and unique properties that make them a viable candidate to be considered for the final hypothesis. We apply the learning algorithm to the hypothesis set and then choose a specific function from the hypothesis set. In terms of examples, the Hypothesis set could be linear regression and the learning algorithm could be gradient descent or the hypothesis set could be neural networks and the learning algorithm could be back propagation. Therefore, in order words, hypothesis set is a set of similar functions which have been shown to have good results under specific conditions and the learning algorithm is the algorithm that will do the actual searching." https://medium.com/technology-nineleaps/what-is-machine-lear...
I agree with you, I don't find talking about "hypothesis sets" to be at all enlightening. To me it sounds like needless jargon and it is strange to see even this amount of effort expended to use it. Maybe we are missing something here though.
>"Hypothesis set is the set of functions that have some common and unique properties that make them a viable candidate to be considered for the final hypothesis. We apply the learning algorithm to the hypothesis set and then choose a specific function from the hypothesis set. In terms of examples, the Hypothesis set could be linear regression and the learning algorithm could be gradient descent or the hypothesis set could be neural networks and the learning algorithm could be back propagation. Therefore, in order words, hypothesis set is a set of similar functions which have been shown to have good results under specific conditions and the learning algorithm is the algorithm that will do the actual searching." https://medium.com/technology-nineleaps/what-is-machine-lear...
I agree with you, I don't find talking about "hypothesis sets" to be at all enlightening. To me it sounds like needless jargon and it is strange to see even this amount of effort expended to use it. Maybe we are missing something here though.
Soneone must be working on this.