Questions tagged [artificial-intelligence]

Artificial Intelligence (AI) is a topic in computer science that deals with the study / creation of intelligent machines. Use this tag for on-topic questions that have an AI aspect.

Filter by
Sorted by
Tagged with
0
votes
1answer
55 views

What is the distribution of a q-matrix in q learning?

Quick question, what is the distribution of a q-matrix in standard q learning? As a q-matrix, lets assume a 2x2 matrix with states 1 and 2, and actions A and B. And lets further assume that In state 1,...
1
vote
1answer
41 views

Artificial Datasets; useful for Ai purposes, what about Ai applications in other fields of science?

In Artificial Intelligence, it's common to create sample 'fake' datasets and use them for the purpose of making more efficient algorithms from classification to regression. Datasets with data points ...
1
vote
0answers
24 views

Answer Set Programming - Make a Fact INVALID [closed]

I have a question regarding Answer Set Programming on how to make an existing fact invalid, when there is already (also) a default statement present in the Knowledge Base. For example, there are two ...
0
votes
0answers
554 views

Probability Scores threshold usually used in Deep Learning for an Object Recognition task

I am working on a Faster RCNN project. I have launched the algorithm and obtained all the bounding box proposals. Each one has a certain probability score: My question is: What is the probability ...
2
votes
0answers
35 views

Backprop working on output layer but not hidden layer [duplicate]

I wrote a program to classify MNIST with a vanilla neural net using sigmoid activation and back-propagation training. I tried to work through the math myself (because I want to understand things ), ...
2
votes
0answers
43 views

Neural Networks for predicting Energy at particular date

I am trying to predict Solar Energy value at particular date.So,for this I am applying Artificial Neural Networks model.I am having problem in deciding activation function. Since sigmoid function ...
3
votes
0answers
1k views

Algorithm to detect time series anomalies (outliers) (using Apache Spark)

I am currently new to machine learning and I will be working on a project that involves using a Machine Learning library to detect and alert about possible anomalies. I will be using Apache Spark and ...
1
vote
0answers
111 views

What's Libratus made of?

I'm trying to understand how Libratus is working. I found that there were 3 main parts, one using counterfactual regret minimization to learn to play from scratch. an end-game solver as well as ...
0
votes
1answer
168 views

Combining heuristics when ranking news feed items

We have a news feed, and we want to surface items to the user based on a number of criteria. Certain items will be surfaced because of factor A, another because of factor B, and yet another because of ...
0
votes
1answer
71 views

Almost all predictions of a SVM are positives(or are all negatives)

I'm facing a binary classification problem using svm light. However using 5-fold-validation I noticed that later I train SVM with training set (Half positive and half negative samples about) the ...
3
votes
1answer
571 views

Is it possible to create a design of a web page using machine learning? Like generating CSS styles, assuming that we already had HTML

There are many machine learning algorithms to generate music, like Magenta and GRUV. I want to know if it is possible to create algorithms like these but for generating styles for webpages.
1
vote
1answer
372 views

Deep Learning for sequences

I want to use deep learning techniques to perform better inference tasks than Hidden Markov Models (which is a shallow model)? I was wondering what is the state-of-the art deep learning model to ...
1
vote
3answers
96 views

Machine Learning that improves our ML algorithms?

I know very little about ML, all I know is what I read on Flipboard or watch on youtube. So from what I know I think ML is a series of algorithms based on statistics and evolution, such that they try ...
-1
votes
1answer
37 views

A literature reference for a problem - clustering of incoming data, improving approximation model

I need to know if the following problem was already adressed anywhere (and if so, then how is it called in literature). Lets say, that we do have clustered datapoints (based on some distance function,...
1
vote
1answer
531 views

How to build a machine learning system (smart system) that updates automatically?

I've been doing machine learning. I have done lots of learning related to data analysis and ML algorithms, and I've got very good results and I understand the algorithms. However, my approaches are ...
0
votes
1answer
828 views

Update of the cell state functions in LSTM RNNs - Interplay of sigmoid and tanh

In trying to get some sort of intuition into what goes on inside an LSTM, there is a step that has the potential to make things fall in place nicely. Here is a diagram from this tutorial ...
0
votes
1answer
100 views

S.O.S Beginner in Data Science and Needs Guidance [closed]

I hope I'm in the right place to post my first query here, and to to be brief, I'm an electrical engineering student, working on a task of "Monitoring electrical machines through Partial Discharge ...
0
votes
1answer
2k views

How do weka classifiers deal with missing values? [closed]

I tried using a training set that has missing values. I applied filters (like replace missing data) and then after there were no more missing data I applied naive bayes, trees etc... I thought this ...
1
vote
0answers
180 views

Why doesn't the use of a forget gate in LSTMs cause vanishing/dying gradients? [duplicate]

I put together some math to show what I'm talking about: https://drive.google.com/file/d/0BwbWRPtraa2zeDhaUWFUVl94ZUk/view?usp=sharing TL;DR: the earlier the timestep, the more number of forget gate ...
4
votes
0answers
875 views

Why is the derivative of the LSTM cell state w.r.t. to the previous cell state equal to the forget gate?

I keep seeing this online, on Quora and Machine Learning subreddits but I don't get it. Here's some basic math to show otherwise: We use this equation for the cell state: $c_t = f_t \odot c_t\__1 + ...
0
votes
1answer
181 views

what are mixed variables in data mining?

I read that neural networks, SVM and neuro-fuzzy don't support "mixed variables." So what are those exactly? Does it refer to mixed types (numeric and non-numeric)? And if so, does that mean the ...
5
votes
1answer
964 views

If we primarily use LSTMs over RNNs to solve the vanishing gradient problem, why can't we just use ReLUs/leaky ReLUs with RNNs instead?

RNNs as in: Recurrent Neural Networks LSTMs as in: Long-Short Term Memory Units ReLU as in: Rectified Linear Units Leaky ReLU as in: Modified ReLUs that don't "die" when negative values are ...
0
votes
1answer
22 views

How do data mining classifiers behave when we add training samples to previously established training models?

I have yet to choose a classifier to get my model but I wanted to see which possible classifiers fit what I'm looking for. In fact, I need an algorithm to establish offline training this way: The ...
2
votes
2answers
359 views

Why does this value iteration example converge in a finite number of steps?

Could someone help me understand why value iteration converges for state C in 3 steps, and in 4 steps for everything else? Why not infinite?
2
votes
0answers
145 views

Understanding the second hidden layers of convnets

Having studied ordinary fully connected ANNs, I am starting to study convnets. I am struggling to understand how hidden layers connect. I do understand how the input matrix forward feeds a smaller ...
1
vote
1answer
149 views

Misunderstanding of the gradient calculation

I'm trying to understand how loss_metric class in dlib calculates the gradient. Here is the code(full version): ...
6
votes
2answers
6k views

Backpropagation algorithm NN with Rectified Linear Unit (ReLU) activation

I am trying to follow a great example in R by Peng Zhao of a simple, "manually"-composed NN to classify the iris dataset into the three different species (setosa, ...
1
vote
0answers
233 views

Oblique random forest with ridge,svm, pls are resulting lesser accuracy than random forests

I am having 20 features with both discrete values and continuous values attributes. I am trying to compare the performance of random forest and oblique random forest. ORF usually performs better than ...
3
votes
1answer
1k views

Struggling to make a neural network mimic a basic if statement

I want to make a neural network that can satisfy the following conditions but the neural network would never get close to converging. It was a ReLu neural network with sigmoid on the output ...
6
votes
2answers
153 views

Best ANN Architecture for high-energy physics problem

First off, a disclaimer: I'm not sure if this is the right Stack Exchange for this question, but I'm not aware of a machine learning specific SE. I am doing research into characterising particle jets ...
6
votes
1answer
680 views

Backpropagation algorithm in neural networks (NN) with logistic activation function

In this Coursera course by Geoffrey Hinton, the backpropagation algorithm is described starting at min 8 of this video, and when completed it looks like this: The slides can be found here. Now, the ...
4
votes
2answers
381 views

lifetime of fraud detection models

Suppose we are building/testing a fraud detection model for a specific credit card/ or a quick cash loan business. We have a lot of data to play with (say past 5years), and after careful preprocessing,...
0
votes
1answer
98 views

Extract the most important for description of the object real values

I want to implement convolutional neural network for extracting real values of the features from the image. I understand that metric learning network tries to learn the most important things of the ...
5
votes
3answers
23k views

What is the difference between bagging and random forest if only one explanatory variable is used?

" The fundamental difference between bagging and random forest is that in Random forests, only a subset of features are selected at random out of the total and the best split feature from the subset ...
5
votes
1answer
200 views

Recommended Mathematics electives for Machine Learning [closed]

I'm a Statistics and CS double major and I must take two more math electives to complete my degree. I have four choices for the Math courses I could take and I was wondering which of the two would be ...
0
votes
1answer
1k views

How to compare two data sets to know if they are not similar?

I want to write a program which when given two data sets, should be able to tell whether the data sets differ significantly or are roughly similar. Details on the two data sets: Both data sets will ...
7
votes
4answers
438 views

What is the difference between artificial intelligence and machine intelligence?

I have read the term "machine intelligence" in a few places, e.g. https://web.archive.org/web/20170219022131/https://research.google.com/pubs/MachineIntelligence.html: Research at Google is at the ...
1
vote
1answer
149 views

Probabilistic Methods vs Q-Learning Technique

I have a confusion about the relationship between Q-learning and the probabilistic methods. Normally probabilistic methods are used to make intelligent decision even the problem is incomplete or ...
1
vote
0answers
69 views

Machine Learning: Is exploring learning rate manually still necessary with an exponential decaying learning rate?

If we have an initial learning rate high enough and a suitable decay factor for exponentially decaying the learning rate over a certain number of epoch, is it still need for us to manually explore the ...
0
votes
0answers
34 views

Is there an algorithm to transform arguments from text to “standard form”?

Consider the following deductive argument, in the form of a paragraph: Drugs use should be legalised, because it is an attack against individual freedom, which is a founding element of our ...
0
votes
1answer
276 views

Dimensionality Reduction of Self Organising Maps

I've probably read any article on dimensionality reduction of Self Organising Maps but just couldn't fully comprehend this process. My understanding so far is: SOM are two-layer networks, ...
3
votes
1answer
2k views

Is it still worth going into machine learning/AI? [closed]

I am a high school senior about to start my undergraduate education. I've done an internship for the past two years working with constitutional neural networks and RNNs. I love doing research, and I ...
0
votes
2answers
4k views

Disadvantage of ANN model

Other than ANN inconsistent prediction performance, What is other ANN disadvantage and weakness?
0
votes
1answer
90 views

ANN produces different result every time it's run

I tried an artificial neural network (ANN) model. Using same data set, it gives a different answer every time I run it in MATLAB. Does anyone why this happens and can suggested the best way to analyze ...
2
votes
3answers
758 views

Average value prediction for Artificial Neural Network

In some research paper, there are researcher used taking ANN prediction by run it multiple time and find the average result for prediction. Is it necessary to make it that way?
1
vote
0answers
1k views

Architecture of the Triplet Neural Network

I want to implement face recognition neural network like in this topic(Step 3: Encoding Faces) using dlib library. I already conducted a some research and found out that it's triplet neural network ...
0
votes
1answer
154 views

When is evolutionary algorithm useless? [closed]

Is there any specific reasons why the evolutionary algorithm is an inappropriate method to use when searching for a key to decrypt a coded message. When there are billions of wrong answers and only ...
1
vote
2answers
65 views

Accounting For Two Teams In Training Data Set

For my ML course, I am planning on building a soccer match predictor using ANN. Some of the input variables I have chosen are: Form in last 5 games Current Table Position Number of Injuries Club ...
1
vote
1answer
65 views

Can you know in advance whether machine learning is going to work for a problem?

Machine learning is in fashion these days in many industries. So business folks think it can be applied to anything to make things great again. My experience tells me that there are problems where it ...
2
votes
1answer
148 views

Transfer Function on Neural Network

Do different Transfer Function produce different prediction in neural network model? How do we know which transfer function suitable for the data we used?