artificial-intelligence

How are neural networks used when the number of inputs could be variable?

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问题 All the examples I have seen of neural networks are for a fixed set of inputs which works well for images and fixed length data. How do you deal with variable length data such sentences, queries or source code? Is there a way to encode variable length data into fixed length inputs and still get the generalization properties of neural networks? 回答1: You would usually extract features from the data and feed those to the network. It is not advisable to take just some data and feed it to net. In

How to optimally solve the flood fill puzzle?

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I like playing the puzzle game Flood-It, which can be played online at: https://www.lemoda.net/javascript/flood-it/game.html It's also available as an iGoogle gadget. The aim is to fill the whole board with the least number of successive flood-fills. I'm trying to write a program which can solve this puzzle optimally. What's the best way to approach this problem? Ideally I want to use the A* algorithm, but I have no idea what should be the function estimating the number of steps left. I did write a program which conducted a depth-4 brute force search to maximize the filled area. It worked

Single layer neural network [closed]

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问题 For the implementation of single layer neural network, I have two data files. In: 0.832 64.643 0.818 78.843 Out: 0 0 1 0 0 1 The above is the format of 2 data files. The target output is "1" for a particular class that the corresponding input belongs to and "0" for the remaining 2 outputs. The problem is as follows: Your single layer neural network will find A (3 by 2 matrix) and b (3 by 1 vector) in Y = A*X + b where Y is [C1, C2, C3]' and X is [x1, x2]'. To solve the problem above with a

Higher-order unification

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问题 I'm working on a higher-order theorem prover, of which unification seems to be the most difficult subproblem. If Huet's algorithm is still considered state-of-the-art, does anyone have any links to explanations of it that are written to be understood by a programmer rather than a mathematician? Or even any examples of where it works and the usual first-order algorithm doesn't? 回答1: State of the art — yes, so far as I know all algorithms more or less take the same shape as Huet's (I follow

How to create a smart chat-bot? [closed]

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问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 4 years ago . I know that it's still an open problem so I don't expect to see complete answers here. I just want to find some approaches to solve the next problem: I have a model (assume that is's bot's memory), and different words are associated with different objects in the model. Speaking

What is the difference between a feature and a label?

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I'm following a tutorial about machine learning basics and there is mentioned that something can be a feature or a label . From what I know, a feature is a property of data that is being used. I can't figure out what the label is, I know the meaning of the word, but I want to know what it means in the context of machine learning. Briefly, feature is input; label is output. This applies to both classification and regression problems. A feature is one column of the data in your input set. For instance, if you're trying to predict the type of pet someone will choose, your input features might

Neural Network example in .NET [closed]

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Any good tutorial with source that will demonstrate how to develop neural network (step bay step for dummies ;-)) Here is good example: Brainnet 1 - A Neural Netwok Project - With Illustration And Code - Learn Neural Network Programming Step By Step And Develop a Simple Handwriting Detection System that will demonstrate some practical uses of neural network programming. There's a really good article on CodeProject: Image Recognition with Neural Networks . Here is an online course on C# neural network programming. http://www.heatonresearch.com/course/intro-neural-nets-cs An interesting tutorial

Open Source Neural Network Library [closed]

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I am looking for an open source neural network library. So far, I have looked at FANN, WEKA, and OpenNN. Are the others that I should look at? The criteria, of course, is documentation, examples, and ease of use. Last update: 2019/01/07 (I will update this answer from time to time...) Simple Implementations of Neural Networks FANN is a very popular implementation in C/C++ and has bindings for many other languages. I think WEKA hasn't got a very good implementation for neural networks. There is a better library for Java (and C#): Encog . In scikit-learn (Python) 0.18 (current developement

How to get a single entity from an image?

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I am using this image. I would like to have only the human part from this image. I don't want the background of this image. How to do this? Any logic, links or the best and simple way? here is the thing i want Link but i want this in objective c There is no easy and fast way to satisfy your requirements. For the beginning you can learn how to detect objects in OpenCV . After this you can check haarcascade_fullbody.xml from OpenCV sources. This cascade is for detecting bodies, open it in text editor, there is additional information in header. Anyway, I'm not sure that existing cascade is too

Any tutorials for developing chatbots? [closed]

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问题 As a engineering student, I would like to make a chat bot using python. So, I searched a lot but couldn't really find stuff that would teach me or give me some concrete information to build a intelligent chat bot. I would like to make a chatbot that gives human-like responses (Simply like a friend chatting with you). I am currently expecting it to be as just a software on my laptop (would like to implement in IM, IRC or websites later). So, I am looking for a tutorial/ any other information