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Results tagged with machine-learning
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For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.
2
votes
How to prevent overfitting in stacked models?
The effectiveness of dividing training data and piping divisions into networks for independent training, although possibly an effective workaround for specific cases, is not indicative of a robust sol …
- 7,513
1
vote
Machine learning to detect wrong address data
The comments are off base. Having worked in validation of data as a consultant for Nasdac, Amex, and Lexis Nexis I can tell you that using the UNIX sed -r or pcrelib is insufficient to do a stellar c …
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0
votes
What is a "generalized" machine learning algorithm?
Using the adjective generalized with algorithms, routines, or functions is obscure. The more appropriate term is generic.
Generics began with early loaders, before full fledged operating systems wer …
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2
votes
Weighing connections between two users using machine learning
The question might be improved so that the answer can be more specific by defining two things more rigorously.
Strength of the connection
What the automation must infer from that value
Learning, Cor …
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1
vote
Accepted
How to use a Generative Adversarial Network to generate images for developmental analysis?
A generative adversarial network is probably not the best approach for generating the images desired. We can assume from the comments that the data is not collected. That's a good thing, because a s …
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3
votes
Why do we need floats for using neural networks?
Floating Point Hardware
There are three common floating point formats used to approximate real numbers used in digital arithmetic circuitry. These are defined in IEEE 754, a standard that was adopte …
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0
votes
Accepted
Why do Decision Tree Learning Algorithm preferably outputs the smallest Decision Tree?
Consider the LCD (least common denominator) principle in algebra. A larger denominator would work for most processes for which the LCD would be calculated, however the least is the one used by convent …
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0
votes
Is it possible to write an adaptive parser?
The parsing of linguistic units from streams of speech by the human brain is an existing system that can be studied, and it is a legitimate proof of concept. A working brain adapts to changes in volu …
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1
vote
Accepted
Can ML/AI understand incomplete constructs like humans?
Central Questions
Can ML/AI understand incomplete constructs like humans?
Do humans have some inherent experiences in life which makes AI incapable of performing [some capacities of human intelligen …
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0
votes
Accepted
Machine learning algorithm for xml manipulation
Terminology
There are two uses of the word map in this discussion.
Road maps are construed below as images of road maps.
Mapping input to desired output is the skill the system must learn.
The se …
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4
votes
Accepted
How can a neural network approximate all functions when the weights are not allowed to grow ...
What is Proven
The question references the proof of Approximation by Superpositions of a Sigmoidal Function, G. Cybenko, 1989, Mathematics of Control, Signals, and Systems.
The 1989 proof stated that …
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0
votes
How can I minimize the number of answers that are relevant to a machine learning model?
The Problem Statement
It does not appear from the wording in the question that the semantics of the language in the questionnaire will be processed, so no knowledge of the associations in questionnai …
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2
votes
Reinforcement learning objective as conditional expectations
In the YouTube depiction of CS294-112 fall 2017 lecture 3 Reinforcement Learning, Levine, the transition of the finite horizon expected reward to a form where each transition is decoupled from the ent …
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0
votes
I need to predict ball position from set of Images
Requirements Analysis
The term prediction has a temporal element, but the other text in comments indicates that the position of the ball relative to the field of play and goals at the time the image …
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1
vote
Handling emotion in informal text (Hi vs HIIIIII!!!!)?
These kinds of repetitions in text can place recurrence demands on learning algorithms that may or may not be handled without special encoding.
Hi.
Hiiii!
HIIIIIIIII
Hi!!!!!!!!!!!!!!
These have th …
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